def main():
parser = argparse.ArgumentParser()
parser.add_argument('cells_csv', help='CSV containing cell metadata')
parser.add_argument('connections_h5',
help='HDF5 file containing cell connectivity')
parser.add_argument('network_vtk_file', help='.vtk output file')
parser.add_argument('--manifest')
parser.add_argument('--morphology_vtk_file')
args = parser.parse_args()
# read in the cell CSV
with open(args.cells_csv, 'r') as f:
r = csv.DictReader(f)
cells = list(r)
# read in the connections from the H5 file
h5u = Hdf5Util()
connections = h5u.read(args.connections_h5)
# write out the results
write_network_vtk(args.network_vtk_file, cells, connections)
if args.manifest:
config = ju.read(args.manifest)
manifest = Manifest(config['manifest'],
relative_base_dir=os.path.dirname(args.manifest))
write_morphology_vtk(args.morphology_vtk_file, cells, manifest)
def load_connectivity(self):
'''
load the connectivity matrix from the hdf5 file in the CSR format - efficient for large networks
'''
h5u = Hdf5Util()
con_path = self.description.manifest.get_path('CONNECTIONS')
con = h5u.read(con_path)
return con
# cell positions
positions = np.random.random((N, 3))
# initialize the network
net = Network()
# add some populations
net.add_population(N_inh, type='inhibitory')
net.add_population(N_exc, type='excitatory')
# add the connectivity rule
net.connect(random_connectivity)
# build the matrix
cells, connections = net.build()
print len(connections)
# turn it into a sparse matrix
m = construct_matrix(connections)
# the connectivity to hdf5
Hdf5Util().write('connections.h5', m)
cells = pd.DataFrame.from_dict(cells)
cells['x'] = positions[:, 0]
cells['y'] = positions[:, 1]
cells['z'] = positions[:, 2]
cells.to_csv('cells.csv', index=False)