def test_is_single_tree_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_disconnected_components.swc')
ok, ids = io.check.is_single_tree(io.load_data(f))
nt.ok_(not ok)
nt.eq_(ids, [6, 217, 428, 639])
def test_has_all_points_connected_good_data():
f = os.path.join(SWC_PATH, 'Neuron.swc')
ok, ids = io.check.all_points_connected(io.load_data(f))
nt.ok_(ok)
nt.eq_(len(ids), 0)
def test_has_sequential_ids_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_missing_ids.swc')
ok, ids = io.check.has_sequential_ids(io.load_data(f))
nt.ok_(not ok)
nt.ok_(ids == [6, 217, 428, 639])
def _check_file(self, f):
'''Run tests on a morphology file'''
L.info('File: %s', f)
result = True
try:
data = load_data(f)
except Exception as e: # pylint: disable=W0703
L.error('Failed to load data... skipping tests for this file')
L.error(e.args)
return False, {f: OrderedDict([('ALL', False)])}
try:
result &= self._check_loop(data, 'structural_checks')
nrn = fst_core.FstNeuron(data)
result &= self._check_loop(nrn, 'neuron_checks')
except Exception as e: # pylint: disable=W0703
L.error('Check failed:' + str(type(e)) + str(e.args))
result = False
self.summary['ALL'] = result
for m, s in self.summary.items():
self._log_msg(m, s)
return result, {f: self.summary}
def test_has_no_missing_parents_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_missing_parents.swc')
ok, ids = io.check.no_missing_parents(io.load_data(f))
nt.ok_(not ok)
nt.eq_(ids, [6, 217, 428, 639])
def test_has_no_missing_parents_good_data():
f = os.path.join(SWC_PATH, 'Neuron.swc')
ok, ids = io.check.no_missing_parents(io.load_data(f))
nt.ok_(ok)
nt.eq_(len(ids), 0)
def _check_file(self, f):
'''Run tests on a morphology file'''
L.info('File: %s', f)
result = True
try:
data = load_data(f)
except StandardError as e:
L.error('Failed to load data... skipping tests for this file')
L.error(e.message)
return False, {f: OrderedDict([('ALL', False)])}
try:
result &= self._check_loop(data, 'structural_checks')
nrn = fst_core.FstNeuron(data)
result &= self._check_loop(nrn, 'neuron_checks')
except StandardError as e:
L.error('Check failed: %s: %s', type(e), e.message)
result = False
self.summary['ALL'] = result
for m, s in self.summary.iteritems():
self._log_msg(m, s)
return result, {f: self.summary}
def _check_file(self, f):
'''Run tests on a morphology file'''
L.info('File: %s', f)
full_result = True
full_summary = OrderedDict()
try:
data = load_data(f)
except Exception as e: # pylint: disable=W0703
L.error('Failed to load data... skipping tests for this file')
L.error(e.args)
return False, {f: OrderedDict([('ALL', False)])}
try:
result, summary = self._check_loop(data, 'structural_checks')
full_result &= result
full_summary.update(summary)
nrn = fst_core.FstNeuron(data)
result, summary = self._check_loop(nrn, 'neuron_checks')
full_result &= result
full_summary.update(summary)
except Exception as e: # pylint: disable=W0703
L.error('Check failed: %s', str(type(e)) + str(e.args))
full_result = False
full_summary['ALL'] = full_result
for m, s in full_summary.items():
self._log_msg(m, s)
return full_result, {f: full_summary}
def test_is_single_tree_good_data():
f = os.path.join(SWC_PATH, 'Neuron.swc')
ok, ids = io.check.is_single_tree(io.load_data(f))
nt.ok_(ok)
nt.eq_(len(ids), 0)
def test_has_all_points_connected_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_disconnected_components.swc')
ok, ids = io.check.all_points_connected(io.load_data(f))
nt.ok_(not ok)
nt.eq_(ids, [6, 217, 428, 639])
def test_read():
rdw = io.load_data(StringIO(MORPH_ASC), reader='asc')
raw_data = rdw.data_block
eq_(raw_data.shape, (19, 7))
ok_(np.allclose(raw_data[:, COLS.ID], np.arange(0, 19))) # correct ID
# 3 is ID of end of the soma, 2 sections attach to this
ok_(np.count_nonzero(raw_data[:, COLS.P] == 3), 2)
def test_has_finite_length_segments_good_data():
files = [os.path.join(SWC_PATH, f)
for f in ['Neuron.swc',
'sequential_trunk_off_0_16pt.swc',
'sequential_trunk_off_1_16pt.swc',
'sequential_trunk_off_42_16pt.swc']]
for f in files:
ok, ids = io.check.has_all_finite_length_segments(io.load_data(f))
nt.ok_(ok)
nt.ok_(len(ids) == 0)
def test_has_soma_points_good_data():
files = [os.path.join(SWC_PATH, f)
for f in ['Neuron.swc',
'Single_apical.swc',
'Single_basal.swc',
'Single_axon.swc']]
files.append(os.path.join(H5V1_PATH, 'Neuron_2_branch.h5'))
for f in files:
nt.ok_(io.check.has_soma_points(io.load_data(f)))
def test_has_finite_radius_neurites_good_data():
files = [os.path.join(SWC_PATH, f)
for f in ['Neuron.swc',
'Single_apical.swc',
'Single_basal.swc',
'Single_axon.swc']]
files.append(os.path.join(H5V1_PATH, 'Neuron_2_branch.h5'))
for f in files:
ok, ids = io.check.has_all_finite_radius_neurites(io.load_data(f))
nt.ok_(ok)
nt.ok_(len(ids) == 0)
def test_read():
rdw = io.load_data(StringIO(MORPH_ASC), reader='asc')
raw_data = rdw.data_block
eq_(raw_data.shape, (19, 7))
ok_(np.allclose(raw_data[:, COLS.ID], np.arange(0, 19))) # correct ID
# 3 is ID of end of the soma, 2 sections attach to this
ok_(np.count_nonzero(raw_data[:, COLS.P] == 3), 2)
neuron = load_neuron(StringIO(MORPH_ASC), reader='asc')
assert_array_equal(neuron.neurites[0].root_node.points[:, COLS.XYZ],
[[0., 5., 0.], [2., 9., 0.], [0., 13., 0.],
[2., 13., 0.], [4., 13., 0.]])
def test_has_finite_length_segments_bad_data():
files = [os.path.join(SWC_PATH, f)
for f in ['Neuron_zero_length_segments.swc',
'Single_apical.swc',
'Single_basal.swc',
'Single_axon.swc']]
bad_segs = [[(4, 5), (215, 216),
(426, 427), (637, 638)],
[(4, 5)],
[(4, 5)],
[(4, 5)]]
for i, f in enumerate(files):
ok, ids = io.check.has_all_finite_length_segments(io.load_data(f))
nt.ok_(not ok)
nt.assert_equal(ids, bad_segs[i])
def test_has_sequential_ids_good_data():
files = [os.path.join(SWC_PATH, f)
for f in ['Neuron.swc',
'Single_apical_no_soma.swc',
'Single_apical.swc',
'Single_basal.swc',
'Single_axon.swc',
'Neuron_zero_radius.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']
]
for f in files:
ok, ids = io.check.has_sequential_ids(io.load_data(f))
nt.ok_(ok)
nt.ok_(len(ids) == 0)
INIT_IDS = [[4, 215, 426, 637],
[],
[4],
[4],
[4],
[2, 10],
[3, 11],
[44, 52],
[4]]
_path = os.path.dirname(os.path.abspath(__file__))
DATA_PATH = os.path.join(_path, '../../../test_data')
SWC_PATH = os.path.join(DATA_PATH, 'swc')
RAW_DATA = [io.load_data(f) for f in FILES]
NO_SOMA_RAW_DATA = io.load_data(NO_SOMA_FILE)
class MockNeuron(object):
def __init__(self, trees):
self.neurites = trees
def test_get_soma_ids():
for i, d in enumerate(RAW_DATA):
nt.ok_(utils.get_soma_ids(d) == SOMA_IDS[i])
def test_get_initial_neurite_segment_ids():
for i, d in enumerate(RAW_DATA):
def test_neuron_name():
d = _io.load_data(FILENAMES[0])
nrn = _core.FstNeuron(d, '12af3rg')
nt.eq_(nrn.name, '12af3rg')
def test_load_neurolucida_ascii():
f = os.path.join(NEUROLUCIDA_PATH, 'sample.asc')
ascii = io.load_data(f)
ok_(isinstance(ascii, DataWrapper))
eq_(len(ascii.data_block), 18)
from neurom.core.tree import Tree
from neurom import segments as seg
from neurom import iter_neurites
import math
from itertools import izip
class MockNeuron(object):
pass
DATA_PATH = './test_data'
SWC_PATH = os.path.join(DATA_PATH, 'swc/')
data = io.load_data(SWC_PATH + 'Neuron.swc')
neuron0 = make_neuron(data)
tree0 = neuron0.neurites[0]
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]))
def test_load_neurolucida_ascii():
f = os.path.join(NEUROLUCIDA_PATH, 'sample.asc')
with warnings.catch_warnings(record=True):
ascii = io.load_data(f)
ok_(isinstance(ascii, DataWrapper))
eq_(len(ascii.data_block), 18)
def test_load_neurolucida_ascii():
f = os.path.join(NEUROLUCIDA_PATH, 'sample.asc')
ascii = io.load_data(f)
ok_(isinstance(ascii, DataWrapper))
eq_(len(ascii.data_block), 18)
def test_neuron_name():
d = _io.load_data(FILENAMES[0])
nrn = _core.FstNeuron(d, '12af3rg')
nt.eq_(nrn.name, '12af3rg')
def test_has_soma_points_bad_data():
f = os.path.join(SWC_PATH, 'Single_apical_no_soma.swc')
nt.ok_(not io.check.has_soma_points(io.load_data(f)))
def test_has_finite_radius_neurites_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_zero_radius.swc')
ok, ids = io.check.has_all_finite_radius_neurites(io.load_data(f))
nt.ok_(not ok)
nt.ok_(ids == [194, 210, 246, 304, 493])
