# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with DeNSE. If not, see <http://www.gnu.org/licenses/>.
import btmorph2
import numpy
import matplotlib.pyplot as plt
from matplotlib.pyplot import ion
ion()
#Import morphology from swc file
neuron1 = btmorph2.NeuronMorphology("lateral/retina1.swc")
# """ get the total length, a scalar morphometric feature """
total_length = neuron1.total_length()
print('Total neurite length=%f', total_length)
# """ get the topological measure of leaf node in the tree"""
no_terminals = neuron1.no_terminals()
print('Number of terminals=%f', no_terminals)
bif_nodes = neuron1._bif_points
term_nodes = neuron1._end_points
all_nodes = bif_nodes + term_nodes
total_length = 0
all_segment_lengths = []
for node in all_nodes:
print(swc_file)
# ds.reset_kernel()
return swc_file
if __name__ == '__main__':
kernel = {
"seeds": [33, 345, 17, 193, 177],
"num_local_threads": 5,
"environment_required": False
}
swc_file = run_dense(neuron_params)
import btmorph2
import matplotlib.pyplot as plt
neuron1 = btmorph2.NeuronMorphology(
os.path.join(swc_file, "morphology.swc"))
total_length = neuron1.total_length()
print('Total neurite length=%f', total_length)
no_terminals = neuron1.no_terminals()
# plt.figure()
# neuron1.plot_dendrogram()
# plt.savefig("dendrogram_low.pdf", format="pdf", dpi=300)
# plt.show()
# plt.figure()
neuron1.plot_2D()
plt.savefig("neuron2.pdf", format="pdf", dpi=300)
plt.show(block=True)
# (at your option) any later version.
#
# DeNSE is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with DeNSE. If not, see <http://www.gnu.org/licenses/>.
import btmorph2
import numpy
import sys
import matplotlib.pyplot as plt
neuron1 = btmorph2.NeuronMorphology(sys.argv[1])
""" get the total length, a scalar morphometric feature """
total_length = neuron1.total_length()
print('Total neurite length=%f' % total_length)
""" get the topological measure of leaf node in the tree"""
no_terminals = neuron1.no_terminals()
print('Number of terminals=%f' % no_terminals)
bif_nodes = neuron1._bif_points
term_nodes = neuron1._end_points
all_nodes = bif_nodes + term_nodes
total_length = 0
all_segment_lengths = []
for node in all_nodes:
all_segment_lengths.append(neuron1.get_segment_pathlength(node))
total_length = total_length + all_segment_lengths[-1]
print('total_length=', total_length)