def test_assign_complex_attr(self):
"""
Test scientific methods are executed
"""
default_cortex = surfaces.Cortex.from_file()
default_cortex.coupling_strength = 0.0121
self.assertTrue(default_cortex.local_connectivity is None)
grey_matter = surfaces.LocalConnectivity(load_default=True, surface=default_cortex, cutoff=2)
default_cortex.local_connectivity = grey_matter
default_cortex.compute_local_connectivity()
self.assertTrue(default_cortex.local_connectivity is not None)
def test_assign_complex_attr(self):
"""
Test scientific methods are executed
"""
local_coupling_strength = 0.0121
grey_matter = surfaces.LocalConnectivity(cutoff=10.0)
default_cortex = surfaces.Cortex(coupling_strength=local_coupling_strength)
#self.assertTrue(default_cortex.local_connectivity is None)
default_cortex.local_connectivity = grey_matter
#default_cortex.region_average = default_cortex.region_mapping
default_cortex.compute_local_connectivity()
self.assertTrue(default_cortex.local_connectivity is not None)
def cdata2local_connectivity(local_connectivity_data,
meta,
storage_path,
expected_length=0):
"""
From a CData entry in CFF, create LocalConnectivity entity.
"""
##### expected_length = cortex.region_mapping.shape[0]
tmpdir = os.path.join(
gettempdir(),
local_connectivity_data.parent_cfile.get_unique_cff_name())
LOG.debug("Using temporary folder for Local Connectivity import: " +
tmpdir)
_zipfile = ZipFile(local_connectivity_data.parent_cfile.src, 'r',
ZIP_DEFLATED)
local_connectivity_path = _zipfile.extract(local_connectivity_data.src,
tmpdir)
gid = dao.get_last_data_with_uid(meta[constants.KEY_SURFACE_UID],
surfaces.CorticalSurface)
surface_data = ABCAdapter.load_entity_by_gid(gid)
local_connectivity = surfaces.LocalConnectivity()
local_connectivity.storage_path = storage_path
local_connectivity_data = read_matlab_data(local_connectivity_path,
constants.DATA_NAME_LOCAL_CONN)
if local_connectivity_data.shape[0] < expected_length:
padding = sparse.csc_matrix(
(local_connectivity_data.shape[0],
expected_length - local_connectivity_data.shape[0]))
local_connectivity_data = sparse.hstack(
[local_connectivity_data, padding])
padding = sparse.csc_matrix(
(expected_length - local_connectivity_data.shape[0],
local_connectivity_data.shape[1]))
local_connectivity_data = sparse.vstack(
[local_connectivity_data, padding])
local_connectivity.equation = None
local_connectivity.matrix = local_connectivity_data
local_connectivity.surface = surface_data
uid = meta[constants.KEY_UID] if constants.KEY_UID in meta else None
if os.path.isdir(tmpdir):
shutil.rmtree(tmpdir)
return local_connectivity, uid
def test_cortexdata(self):
dt = surfaces.Cortex()
## Initialize Local Connectivity, to avoid long computation time.
reader = readers.File(folder_path="surfaces/cortex_reg13")
dt.local_connectivity = surfaces.LocalConnectivity()
dt.local_connectivity.matrix = reader.read_data("nearest_neighbour.mat", "LocalCoupling")
dt.configure()
summary_info = dt.summary_info
self.assertTrue(abs(summary_info['Region area, maximum (mm:math:`^2`)'] - 9119.4540365252615) < 0.00000001)
self.assertTrue(abs(summary_info['Region area, mean (mm:math:`^2`)'] - 3366.2542250541251) < 0.00000001)
self.assertTrue(abs(summary_info['Region area, minimum (mm:math:`^2`)'] - 366.48271886512993) < 0.00000001)
self.assertEqual(dt.get_data_shape('vertices'), (16384, 3))
self.assertEqual(dt.get_data_shape('vertex_normals'), (16384, 3))
self.assertEqual(dt.get_data_shape('triangles'), (32760, 3))
def test_cortexdata(self):
dt = surfaces.Cortex(load_default=True)
self.assertTrue(isinstance(dt, surfaces.Cortex))
self.assertTrue(dt.region_mapping is not None)
## Initialize Local Connectivity, to avoid long computation time.
dt.local_connectivity = surfaces.LocalConnectivity(load_default=True)
dt.configure()
summary_info = dt.summary_info
self.assertTrue(
abs(summary_info['Region area, maximum (mm:math:`^2`)'] -
9119.4540365252615) < 0.00000001)
self.assertTrue(
abs(summary_info['Region area, mean (mm:math:`^2`)'] -
3366.2542250541251) < 0.00000001)
self.assertTrue(
abs(summary_info['Region area, minimum (mm:math:`^2`)'] -
366.48271886512993) < 0.00000001)
self.assertEqual(dt.get_data_shape('vertices'), (16384, 3))
self.assertEqual(dt.get_data_shape('vertex_normals'), (16384, 3))
self.assertEqual(dt.get_data_shape('triangles'), (32760, 3))
def test_localconnectivity(self):
dt = surfaces.LocalConnectivity()
self.assertTrue(dt.surface is None)
#Initialise an Integrator
heunint = integrators.HeunDeterministic(dt=2**-4)
#Initialise some Monitors with period in physical time
mon_tavg = monitors.TemporalAverage(period=2**-2)
mon_savg = monitors.SpatialAverage(period=2**-2)
mon_eeg = monitors.EEG(period=2**-2)
#Bundle them
what_to_watch = (mon_tavg, mon_savg, mon_eeg)
#Initialise a surface
local_coupling_strength = numpy.array([0.0121])
grey_matter = surfaces.LocalConnectivity(equation=equations.Gaussian(),
cutoff=60.0)
grey_matter.equation.parameters['sigma'] = 10.0
grey_matter.equation.parameters['amp'] = 0.0
default_cortex = surfaces.Cortex(local_connectivity=grey_matter,
coupling_strength=local_coupling_strength)
#Define the stimulus
eqn_t = equations.Gaussian()
eqn_t.parameters["amp"] = 0.0
eqn_t.parameters["midpoint"] = 8.0
eqn_x = equations.Gaussian()
eqn_x.parameters["amp"] = -0.0625
eqn_x.parameters["sigma"] = 28.0
