def vol_density(neurite):
"""Volume density of a single neurite."""
try:
volume = convex_hull(neurite).volume
except scipy.spatial.qhull.QhullError:
L.exception('Failure to compute neurite volume using the convex hull. '
'Feature `neurite_volume_density` will return `np.nan`.\n')
return np.nan
return neurite.volume / volume
def test_volume_density_per_neurite():
vol = np.array(_nf.total_volume_per_neurite(NRN))
hull_vol = np.array([convex_hull(n).volume for n in nm.iter_neurites(NRN)])
vol_density = _nf.volume_density_per_neurite(NRN)
nt.eq_(len(vol_density), 4)
nt.ok_(np.allclose(vol_density, vol / hull_vol))
ref_density = [0.43756606998299519, 0.52464681266899216,
0.24068543213643726, 0.26289304906104355]
nt.ok_(np.allclose(vol_density, ref_density))
def test_neurite_volume_density():
vol = np.array(_nf.total_volume_per_neurite(NRN))
hull_vol = np.array([convex_hull(n).volume for n in nm.iter_neurites(NRN)])
vol_density = _nf.neurite_volume_density(NRN)
nt.eq_(len(vol_density), 4)
nt.ok_(np.allclose(vol_density, vol / hull_vol))
ref_density = [
0.43756606998299519, 0.52464681266899216, 0.24068543213643726,
0.26289304906104355
]
assert_allclose(vol_density, ref_density)
def vol_density(neurite):
'''volume density of a single neurite'''
return neurite.volume / convex_hull(neurite).volume
def test_convex_hull_volume():
# This leverages scipy ConvexHull and we don't want
# to re-test scipy, so simply regression test the volume
hull = geom.convex_hull(NRN)
assert_almost_equal(hull.volume, 208641, decimal=0)
def test_convex_hull_points():
# This leverages scipy ConvexHull and we don't want
# to re-test scipy, so simply check that the points are the same.
hull = geom.convex_hull(NRN)
assert np.alltrue(hull.points == NRN.points[:, :3])
def vol_density(neurite):
"""volume density of a single neurite"""
return neurite.volume / convex_hull(neurite).volume
def vol_density(neurite):
'''volume density of a single neurite'''
return neurite.volume / convex_hull(neurite).volume
def test_convex_hull_volume():
# This leverages scipy ConvexHull and we don't want
# to re-test scipy, so simply regression test the volume
hull = geom.convex_hull(NRN)
nt.assert_almost_equal(hull.volume, 208641.65, places=3)
def test_convex_hull_points():
# This leverages scipy ConvexHull and we don't want
# to re-test scipy, so simply check that the points are the same.
hull = geom.convex_hull(NRN)
nt.ok_(np.alltrue(hull.points == NRN.points[:, :3]))
def vol_density(neurite):
"""Volume density of a single neurite."""
return neurite.volume / convex_hull(neurite).volume
