def test_has_sequential_ids_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_missing_ids.swc')
ok, ids = check.has_sequential_ids(load_data(f))
nt.ok_(not ok)
nt.ok_(ids == [6, 217, 428, 639])
def test_has_sequential_ids_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_missing_ids.swc')
ok, ids = check.has_sequential_ids(load_data(f))
nt.ok_(not ok)
nt.ok_(ids == [6, 217, 428, 639])
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 = check.has_all_finite_length_segments(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_(check.has_soma_points(load_data(f)))
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 = check.has_all_finite_length_segments(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_(check.has_soma_points(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 = check.has_all_finite_radius_neurites(load_data(f))
nt.ok_(ok)
nt.ok_(len(ids) == 0)
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 = check.has_all_finite_radius_neurites(load_data(f))
nt.ok_(ok)
nt.ok_(len(ids) == 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 = check.has_all_finite_length_segments(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 = check.has_sequential_ids(load_data(f))
nt.ok_(ok)
nt.ok_(len(ids) == 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 = check.has_all_finite_length_segments(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 = check.has_sequential_ids(load_data(f))
nt.ok_(ok)
nt.ok_(len(ids) == 0)
def load_neuron(filename, tree_action=None):
"""
Loads a neuron keeping a record of the filename.
Args:
filename: the path of the file storing morphology data
tree_action: optional function to run on each of the neuron's
neurite trees.
Raises: SomaError if no soma points in data.
Raises: NonConsecutiveIDsError if filename contains non-consecutive
point IDs
"""
data = load_data(filename)
if not has_sequential_ids(data)[0]:
raise NonConsecutiveIDsError('Non consecutive IDs found in raw data')
nrn = make_neuron(data, tree_action)
nrn.name = os.path.splitext(os.path.basename(filename))[0]
return nrn
def load_neuron(filename, tree_action=None):
"""
Loads a neuron keeping a record of the filename.
Args:
filename: the path of the file storing morphology data
tree_action: optional function to run on each of the neuron's
neurite trees.
Raises: SomaError if no soma points in data.
Raises: NonConsecutiveIDsError if filename contains non-consecutive
point IDs
"""
data = load_data(filename)
if not has_sequential_ids(data)[0]:
raise NonConsecutiveIDsError('Non consecutive IDs found in raw data')
nrn = make_neuron(data, tree_action)
nrn.name = os.path.splitext(os.path.basename(filename))[0]
return nrn
def test_has_soma_points_bad_data():
f = os.path.join(SWC_PATH, 'Single_apical_no_soma.swc')
nt.ok_(not check.has_soma_points(load_data(f)))
def test_has_finite_radius_neurites_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_zero_radius.swc')
ok, ids = check.has_all_finite_radius_neurites(load_data(f))
nt.ok_(not ok)
nt.ok_(ids == [194, 210, 246, 304, 493])
from neurom.analysis.morphtree import n_bifurcations
from neurom.analysis.morphtree import n_terminations
from neurom.analysis.morphtree import trunk_radius
from neurom.analysis.morphtree import trunk_length
from neurom.analysis.morphtree import trunk_direction
from neurom.analysis.morphtree import trunk_elevation
from neurom.analysis.morphtree import trunk_azimuth
from neurom.analysis.morphtree import get_bounding_box
import math
import numpy as np
from itertools import izip
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))
def test_has_soma_points_bad_data():
f = os.path.join(SWC_PATH, 'Single_apical_no_soma.swc')
nt.ok_(not check.has_soma_points(load_data(f)))
'''Calculate inter-segment angles'''
import logging
import numpy as np
from neurom.core.dataformat import COLS
from neurom.io.readers import load_data
from neurom.io.utils import make_neuron
from neurom.analysis.morphtree import i_segment_meander_angle
# root level logger. This would be a top level application logger.
logging.basicConfig()
LOG = logging.getLogger()
LOG.setLevel(logging.DEBUG)
fmt = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
LOG.handlers[0].setFormatter(fmt)
if __name__ == '__main__':
filename = 'test_data/swc/Neuron.swc'
rd = load_data(filename)
nrn = make_neuron(rd)
for tt in nrn.neurites:
print 'Tree ID: {0}, type: {1}'.format(tt.value[COLS.ID], tt.value[COLS.TYPE])
for a in i_segment_meander_angle(tt):
LOG.debug('Angle %f', a)
if np.isnan(a):
LOG.warn('Found NaN angle. Check for zero length segments!')
def test_has_finite_radius_neurites_bad_data():
f = os.path.join(SWC_PATH, 'Neuron_zero_radius.swc')
ok, ids = check.has_all_finite_radius_neurites(load_data(f))
nt.ok_(not ok)
nt.ok_(ids == [194, 210, 246, 304, 493])
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
'''Calculate inter-segment angles'''
import logging
import numpy as np
from neurom.core.dataformat import COLS
from neurom.io.readers import load_data
from neurom.io.utils import make_neuron
from neurom.analysis.morphtree import i_segment_meander_angle
# root level logger. This would be a top level application logger.
logging.basicConfig()
LOG = logging.getLogger()
LOG.setLevel(logging.DEBUG)
fmt = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
LOG.handlers[0].setFormatter(fmt)
if __name__ == '__main__':
filename = 'test_data/swc/Neuron.swc'
rd = load_data(filename)
nrn = make_neuron(rd)
for tt in nrn.neurites:
print 'Tree ID: {0}, type: {1}'.format(tt.value[COLS.ID],
tt.value[COLS.TYPE])
for a in i_segment_meander_angle(tt):
LOG.debug('Angle %f', a)
if np.isnan(a):
LOG.warn('Found NaN angle. Check for zero length segments!')
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 = [load_data(f) for f in FILES]
NO_SOMA_RAW_DATA = load_data(NO_SOMA_FILE)
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_segment_ids():
for i, d in enumerate(RAW_DATA):
nt.ok_(utils.get_initial_segment_ids(d) == INIT_IDS[i])
def _check_trees(trees):
for t in trees:
