simplify range by removing 0 start

examples/external_devices_examples/live_examples/spike_io.py

@@ -196,7 +196,7 @@ def receive_spikes(label, _time, neuron_ids):
 # reaches the end
 loop_forward = []
 loop_backward = []
-for i in range(0, n_neurons - 1):
+for i in range(n_neurons - 1):
     loop_forward.append((i, (i + 1) % n_neurons, weight_to_spike, 3))
     loop_backward.append(((i + 1) % n_neurons, i, weight_to_spike, 3))
 Frontend.Projection(pop_forward, pop_forward,

examples/external_devices_examples/live_examples/spike_io_interactive_demo_with_c_vis.py

@@ -133,7 +133,7 @@ def __init__(self):
                 label='spike_injector_backward')
         else:
             spike_times = []
-            for _ in range(0, self.n_neurons):
+            for _ in range(self.n_neurons):
                 spike_times.append([])
             spike_times[0] = [0]
             spike_times[20] = [(run_time / 100) * 20]
@@ -142,7 +142,7 @@ def __init__(self):
             spike_times[80] = [(run_time / 100) * 80]
             cell_params_forward = {'spike_times': spike_times}
             spike_times_backwards = []
-            for _ in range(0, self.n_neurons):
+            for _ in range(self.n_neurons):
                 spike_times_backwards.append([])
             spike_times_backwards[0] = [(run_time / 100) * 80]
             spike_times_backwards[20] = [(run_time / 100) * 60]
@@ -175,7 +175,7 @@ def __init__(self):
         # it reaches the end
         loop_forward = []
         loop_backward = []
-        for i in range(0, self.n_neurons - 1):
+        for i in range(self.n_neurons - 1):
             loop_forward.append((i, (i + 1) %
                                  self.n_neurons, weight_to_spike, 3))
             loop_backward.append(((i + 1) %

examples/external_devices_examples/live_examples/synfire_if_curr_exp_live.py

@@ -42,7 +42,7 @@
 delay = 17
 
 loopConnections = []
-for i in range(0, nNeurons):
+for i in range(nNeurons):
     singleConnection = (i, ((i + 1) % nNeurons), weight_to_spike, delay)
     loopConnections.append(singleConnection)
 

examples/extra_models_examples/LGN_Izhikevich.py

@@ -63,7 +63,7 @@ def get_mean_rate(numCells, population):
     """
     firing_rate = []      # format = < neuron_id, rate (spikes/ms) >
 
-    for index in range(0, numCells):
+    for index in range(numCells):
         rate = len(population.segments[0].spiketrains[index])/TotalDuration
         firing_rate.append(rate)
 

examples/extra_models_examples/synfire_if_curr_dual_exp.py

@@ -55,7 +55,7 @@ def run_script(*, split: bool = False) -> None:
     delay = 17
 
     loopConnections = []
-    for i in range(0, nNeurons):
+    for i in range(nNeurons):
         singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
         loopConnections.append(singleConnection)
 

examples/synfire_if_cond_exp.py

@@ -41,7 +41,7 @@
 delay = 17
 
 loopConnections = []
-for i in range(0, nNeurons):
+for i in range(nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)
 

examples/synfire_if_curr_exp.py

@@ -42,7 +42,7 @@
 delay = 17
 
 loopConnections = []
-for i in range(0, nNeurons):
+for i in range(nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)
 

examples/synfire_if_curr_exp_get_weights.py

@@ -40,7 +40,7 @@
 delay = 17
 
 loopConnections = []
-for i in range(0, nNeurons):
+for i in range(nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)
 

examples/synfire_if_curr_exp_large_array.py

@@ -41,7 +41,7 @@
 
 connections = []
 reverseConnections = []
-for i in range(0, nNeurons - 1):
+for i in range(nNeurons - 1):
     connections.append((i, (i + 1) % nNeurons, weight_to_spike, delay))
     reverseConnections.append(((i + 1) % nNeurons, i, weight_to_spike, delay))
 

examples/synfire_if_curr_exp_random.py

@@ -41,7 +41,7 @@
 delay = RandomDistribution("uniform", low=1, high=max_delay)
 
 loopConnections = []
-for i in range(0, nNeurons):
+for i in range(nNeurons):
     delay_value = delay.next()
     singleConnection = (i, ((i + 1) % nNeurons), weight_to_spike, delay_value)
     loopConnections.append(singleConnection)

examples/synfire_izk_curr_exp.py

@@ -42,7 +42,7 @@
 delay = 1
 
 loopConnections = []
-for i in range(0, nNeurons):
+for i in range(nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)