Renamed balanced networks of Izhikevich neurons examples. Added bench…

…mark for comparison with CarlSim 4

python/examples/balanced_izh_psc_exp_2s_eval_time.py

@@ -0,0 +1,88 @@
+import sys
+import ctypes
+import neurongpu as ngpu
+from random import randrange
+
+if len(sys.argv) != 2:
+    print ("Usage: python %s n_neurons" % sys.argv[0])
+    quit()
+
+order = int(sys.argv[1])//5
+
+ngpu.SetTimeResolution(1.0)
+
+print("Building ...")
+
+ngpu.SetRandomSeed(1234) # seed for GPU random numbers
+
+sim_time = 10.0 # simulation time in seconds
+
+n_receptors = 2
+
+NE = 4 * order       # number of excitatory neurons
+NI = 1 * order       # number of inhibitory neurons
+n_neurons = NE + NI  # number of neurons in total
+
+CE = 80     # number of excitatory synapses per neuron
+CI = CE//4  # number of inhibitory synapses per neuron
+
+fact=0.42
+Wex = 0.5*fact
+Win = -3.5*fact
+
+tau_plus = 20.0
+tau_minus = 20.0
+lambd = 1.0e-5
+alpha = 1.0
+mu_plus = 1.0
+mu_minus = 1.0
+Wmax = 10.0
+
+syn_group = ngpu.CreateSynGroup \
+            ("stdp", {"tau_plus":tau_plus, "tau_minus":tau_minus, \
+                      "lambda":lambd, "alpha":alpha, "mu_plus":mu_plus, \
+                      "mu_minus":mu_minus,  "Wmax":Wmax})
+
+# poisson generator parameters
+poiss_rate = 20000.0 # poisson signal rate in Hz
+poiss_weight = 0.37*fact
+poiss_delay = 1.0 # poisson signal delay in ms
+
+# create poisson generator
+pg = ngpu.Create("poisson_generator")
+ngpu.SetStatus(pg, "rate", poiss_rate)
+
+# Create n_neurons neurons with n_receptor receptor ports
+neuron = ngpu.Create("izhikevich_psc_exp_2s", n_neurons, n_receptors)
+exc_neuron = neuron[0:NE]      # excitatory neurons
+inh_neuron = neuron[NE:n_neurons]   # inhibitory neurons
+
+# receptor parameters
+
+delay = 2.0
+
+# Excitatory connections
+# connect excitatory neurons to port 0 of all neurons
+# normally distributed delays, weight Wex and CE connections per neuron
+exc_conn_dict={"rule": "fixed_indegree", "indegree": CE}
+exc_syn_dict={"weight": Wex, "delay": delay, "receptor":0,
+              "synapse_group":syn_group}
+ngpu.Connect(exc_neuron, neuron, exc_conn_dict, exc_syn_dict)
+
+
+# Inhibitory connections
+# connect inhibitory neurons to port 1 of all neurons
+# normally distributed delays, weight Win and CI connections per neuron
+inh_conn_dict={"rule": "fixed_indegree", "indegree": CI}
+inh_syn_dict={"weight": Win, "delay":delay, "receptor":1}
+
+ngpu.Connect(inh_neuron, neuron, inh_conn_dict, inh_syn_dict)
+
+
+#connect poisson generator to port 0 of all neurons
+pg_conn_dict={"rule": "all_to_all"}
+pg_syn_dict={"weight": poiss_weight, "delay": poiss_delay, "receptor":0}
+
+ngpu.Connect(pg, neuron, pg_conn_dict, pg_syn_dict)
+
+ngpu.Simulate(sim_time*1000.0)