def saveUVDistanceForPost(filename, name, p_index, c_index):
""" Saves connection length data but for incoming connections of a given
post-synaptic neuron,
name and p_index therefore also refer to the post-synaptic layer """
object = bpy.data.objects[name]
uvs = getUVs(object, p_index)
distances = []
axon_lengths = []
number_particles = len(object.particle_systems[p_index].particles)
for i, p in enumerate(object.particle_systems[p_index].particles):
logger.info('%i / %i' % (i, number_particles))
pre_neurons, synapses = model.getPreIndicesOfPostIndex(c_index, i)
distance = []
axon_length = []
for j in range(len(pre_neurons)):
distance.append(model.CONNECTION_RESULTS[c_index]['d'][pre_neurons[j]][synapses[j]])
axon_length.append(pam.computeDistance_PreToSynapse(c_index, pre_neurons[j], [synapses[j]])[0])
distances.append(np.mean(distance))
axon_lengths.append(np.mean(axon_length))
f = open(filename, 'w')
writer = csv.writer(
f,
delimiter=";",
quoting=csv.QUOTE_NONNUMERIC
)
for i, uv in enumerate(uvs):
#for d in distances[i]:
writer.writerow([uv[0], uv[1], distances[i], axon_lengths[i]])
f.close()
def saveUVDistanceForPost(filename, name, p_index, c_index):
""" Saves connection length data but for incoming connections of a given
post-synaptic neuron,
name and p_index therefore also refer to the post-synaptic layer """
object = bpy.data.objects[name]
uvs = getUVs(object, p_index)
distances = []
axon_lengths = []
number_particles = len(object.particle_systems[p_index].particles)
for i, p in enumerate(object.particle_systems[p_index].particles):
logger.info('%i / %i' % (i, number_particles))
pre_neurons, synapses = model.getPreIndicesOfPostIndex(c_index, i)
distance = []
axon_length = []
for j in range(len(pre_neurons)):
distance.append(model.CONNECTION_RESULTS[c_index]['d'][
pre_neurons[j]][synapses[j]])
axon_length.append(
pam.computeDistance_PreToSynapse(c_index, pre_neurons[j],
[synapses[j]])[0])
distances.append(np.mean(distance))
axon_lengths.append(np.mean(axon_length))
f = open(filename, 'w')
writer = csv.writer(f, delimiter=";", quoting=csv.QUOTE_NONNUMERIC)
for i, uv in enumerate(uvs):
#for d in distances[i]:
writer.writerow([uv[0], uv[1], distances[i], axon_lengths[i]])
f.close()
def saveUVDistance(filename, name, p_index, c_index):
uvs, distances = getUVDistance(name, p_index, c_index)
no_particles = len(bpy.data.objects[name].particle_systems[p_index].particles)
axon_length = [pam.computeDistance_PreToSynapse(c_index, i)[0] for i in range(no_particles)]
f = open(filename, 'w')
writer = csv.writer(
f,
delimiter=";",
quoting=csv.QUOTE_NONNUMERIC
)
for i, uv in enumerate(uvs):
#for d in distances[i]:
writer.writerow([uv[0], uv[1], distances[i], axon_length[i]])
f.close()
def saveUVDistance(filename, name, p_index, c_index):
uvs, distances = getUVDistance(name, p_index, c_index)
no_particles = len(
bpy.data.objects[name].particle_systems[p_index].particles)
axon_length = [
pam.computeDistance_PreToSynapse(c_index, i)[0]
for i in range(no_particles)
]
f = open(filename, 'w')
writer = csv.writer(f, delimiter=";", quoting=csv.QUOTE_NONNUMERIC)
for i, uv in enumerate(uvs):
#for d in distances[i]:
writer.writerow([uv[0], uv[1], distances[i], axon_length[i]])
f.close()