From 5a766b1f4b0be398333393b5d3edb4c24b22a95f Mon Sep 17 00:00:00 2001
From: Thorsten Hater <24411438+thorstenhater@users.noreply.github.com>
Date: Fri, 11 Mar 2022 16:47:23 +0100
Subject: [PATCH] Make brunel.py setup faster. (#1854)
* Make brunel.py setup faster.
* Use one generator for both populations.
---
python/example/brunel.py | 23 ++++++++++++-----------
1 file changed, 12 insertions(+), 11 deletions(-)
diff --git a/python/example/brunel.py b/python/example/brunel.py
index 30dc11e2..37c415cd 100755
--- a/python/example/brunel.py
+++ b/python/example/brunel.py
@@ -1,7 +1,9 @@
#!/usr/bin/env python3
import arbor
-import numpy,argparse
+import argparse
+import numpy as np
+from numpy.random import RandomState
'''
A Brunel network consists of nexc excitatory LIF neurons and ninh inhibitory LIF neurons.
@@ -20,14 +22,12 @@ Call with parameters, for example:
# Samples m unique values in interval [start, end) - gid.
# We exclude gid because we don't want self-loops.
-def sample_subset(gid, start, end, m):
- gen = numpy.random.RandomState(gid+42)
- s = set()
- while len(s) < m:
- val = gen.randint(low=start,high=end)
- if val != gid:
- s.add(val)
- return s
+def sample_subset(gen, gid, start, end, m):
+ idx = np.arange(start, end)
+ if start <= gid < end:
+ idx = np.delete(idx, gid - start)
+ gen.shuffle(idx)
+ return idx[:m]
class brunel_recipe (arbor.recipe):
def __init__(self, nexc, ninh, next, in_degree_prop, weight, delay, rel_inh_strength, poiss_lambda, seed = 42):
@@ -61,12 +61,13 @@ class brunel_recipe (arbor.recipe):
return arbor.cell_kind.lif
def connections_on(self, gid):
+ gen = RandomState(gid + self.seed_)
connections=[]
# Add incoming excitatory connections.
- for i in sample_subset(gid, 0, self.ncells_exc_, self.in_degree_exc_):
+ for i in sample_subset(gen, gid, 0, self.ncells_exc_, self.in_degree_exc_):
connections.append(arbor.connection((i,"src"), "tgt", self.weight_exc_, self.delay_))
# Add incoming inhibitory connections.
- for i in sample_subset(gid, self.ncells_exc_, self.ncells_exc_ + self.ncells_inh_, self.in_degree_inh_):
+ for i in sample_subset(gen, gid, self.ncells_exc_, self.ncells_exc_ + self.ncells_inh_, self.in_degree_inh_):
connections.append(arbor.connection((i,"src"), "tgt", self.weight_inh_, self.delay_))
return connections
--
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