def _update_num_aff_connections(net_id=0, verbose=False):
"""
We need to set for all NormProjections the number of afferent
connections for each projection (across multiple projections,
otherwise pre_rank[i].size() would be sufficient.
Attention:
This function should be used only internally!!! The function is
called during Compiler.compile() call.
"""
# Do we need to execute this procedure?
need_to_execute = False
for proj in Global.projections():
if isinstance(proj, NormProjection):
need_to_execute = True
break
if need_to_execute == False:
return
# iterate over all populations
for pop in Global.populations(net_id):
nb_synapses = np.zeros((pop.size))
# get afferent projections of this layer
aff_proj = Global.projections(net_id, pop.name)
# we accumulate the number of synapses per dendrite
# across all afferent projections of this layer.
for i, proj in enumerate(aff_proj):
# nb synapses per dendrite is oriented at the post_ranks list. If a neuron
# does not receive any connection in THIS projection there is no entry
nb_synapses_per_dend = np.array(proj.nb_synapses_per_dendrite())
if len(nb_synapses_per_dend) == 0:
continue
# Update global count
for idx, rank in enumerate(proj.post_ranks):
nb_synapses[rank] += nb_synapses_per_dend[idx]
# set number of afferent connections for correct normalization
for i, proj in enumerate(aff_proj):
if not isinstance(proj, NormProjection):
continue
if verbose:
print('Update:', proj.pre.name, '->', proj.post.name, '(',
proj.target, ') -- (', i + 1, 'of', len(aff_proj), ')')
if len(proj.post_ranks) != proj.post.size:
print('ranks:', proj.post_ranks)
nb_synapses_per_dend = np.array(proj.nb_synapses_per_dendrite())
if verbose:
print('before:', nb_synapses_per_dend)
for idx, rank in enumerate(proj.post_ranks):
nb_synapses_per_dend[idx] = nb_synapses[rank]
if verbose:
print('after:', nb_synapses_per_dend)
proj.cyInstance.set_semiglobal_attribute_all(
"nb_aff_synapse", nb_synapses_per_dend, "double")
