replace dict() and list() with {} and []

examples/external_devices_examples/live_examples/spike_io.py

@@ -194,8 +194,8 @@ def receive_spikes(label, _time, neuron_ids):
 # Synfire chain connections where each neuron is connected to its next neuron
 # NOTE: there is no recurrent connection so that each chain stops once it
 # reaches the end
-loop_forward = list()
-loop_backward = list()
+loop_forward = []
+loop_backward = []
 for i in range(0, 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))

examples/external_devices_examples/live_examples/spike_io_interactive_demo_with_c_vis.py

@@ -173,8 +173,8 @@ def __init__(self):
         # neuron
         # NOTE: there is no recurrent connection so that each chain stops once
         # it reaches the end
-        loop_forward = list()
-        loop_backward = list()
+        loop_forward = []
+        loop_backward = []
         for i in range(0, self.n_neurons - 1):
             loop_forward.append((i, (i + 1) %
                                  self.n_neurons, weight_to_spike, 3))

examples/external_devices_examples/live_examples/synfire_if_curr_exp_live.py

@@ -35,13 +35,13 @@
                    'v_thresh': -50.0
                    }
 
-populations = list()
-projections = list()
+populations = []
+projections = []
 
 weight_to_spike = 2.0
 delay = 17
 
-loopConnections = list()
+loopConnections = []
 for i in range(0, nNeurons):
     singleConnection = (i, ((i + 1) % nNeurons), weight_to_spike, delay)
     loopConnections.append(singleConnection)

examples/external_devices_examples/motor_example.py

@@ -26,8 +26,8 @@
 connected_chip_coords = {'x': 0, 'y': 0}
 link = 4
 
-populations = list()
-projections = list()
+populations = []
+projections = []
 
 
 input_population = p.Population(6, p.SpikeSourcePoisson(rate=10))

examples/extra_models_examples/stdp_associative_memory.py

@@ -54,8 +54,8 @@
     'v_rest': -70.0,
     'v_thresh': -50.0}
 
-populations = list()
-projections = list()
+populations = []
+projections = []
 
 stimulus = 0
 inhib = 1
@@ -85,8 +85,8 @@
 p_to_inhib_connect = 1.0
 p_from_inhib_connect = 1.0
 
-spikes0 = list()
-teachingSpikes = list()
+spikes0 = []
+teachingSpikes = []
 for i in range(runTime//40):
     spikes0.append(i*40)
 for i in range(runTime//80):
@@ -106,7 +106,7 @@
     arrayEntries.append(newEntry)
 spikeArray = {'spike_times': arrayEntries}
 
-teachlist = list()
+teachlist = []
 for i in range(nSourceNeurons):
     teachlist.append(teachingSpikes)
 teachingSpikeArray = {'spike_times': teachlist}

examples/extra_models_examples/stdp_mad_recurrent_pre_stochastic_multiplicative.py

@@ -41,8 +41,8 @@
     'v_rest': -70.0,
     'v_thresh': -50.0}
 
-populations = list()
-projections = list()
+populations = []
+projections = []
 
 stimulus = 0
 inhib = 1
@@ -52,8 +52,8 @@
 weight_to_force_firing = 15.0
 baseline_excit_weight = 2.0
 
-spikes0 = list()
-teachingSpikes = list()
+spikes0 = []
+teachingSpikes = []
 for i in range(runTime//40):
     spikes0.append(i*40)
 for i in range(runTime//80):
@@ -67,7 +67,7 @@
     arrayEntries.append(newEntry)
 spikeArray = {'spike_times': arrayEntries}
 
-teachlist = list()
+teachlist = []
 for i in range(nSourceNeurons):
     teachlist.append(teachingSpikes)
 teachingSpikeArray = {'spike_times': teachlist}

examples/extra_models_examples/synfire_if_curr_dual_exp.py

@@ -48,13 +48,13 @@ def run_script(*, split: bool = False) -> None:
                        'v_thresh': -50.0
                        }
 
-    populations = list()
-    projections = list()
+    populations = []
+    projections = []
 
     weight_to_spike = 2.0
     delay = 17
 
-    loopConnections = list()
+    loopConnections = []
     for i in range(0, nNeurons):
         singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
         loopConnections.append(singleConnection)

examples/synfire_if_cond_exp.py

@@ -40,7 +40,7 @@
 weight_to_spike = 0.035
 delay = 17
 
-loopConnections = list()
+loopConnections = []
 for i in range(0, nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)

examples/synfire_if_curr_exp.py

@@ -35,13 +35,13 @@
                    'v_thresh': -50.0
                    }
 
-populations = list()
-projections = list()
+populations = []
+projections = []
 
 weight_to_spike = 2.0
 delay = 17
 
-loopConnections = list()
+loopConnections = []
 for i in range(0, nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)

examples/synfire_if_curr_exp_get_weights.py

@@ -33,13 +33,13 @@
                    'v_thresh': -50.0
                    }
 
-populations = list()
-projections = list()
+populations = []
+projections = []
 
 weight_to_spike = 2.0
 delay = 17
 
-loopConnections = list()
+loopConnections = []
 for i in range(0, nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)

examples/synfire_if_curr_exp_large_array.py

@@ -39,8 +39,8 @@
 second_spike_start = delay * nNeurons
 space_between_inputs = delay * nNeurons * 2
 
-connections = list()
-reverseConnections = list()
+connections = []
+reverseConnections = []
 for i in range(0, 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

@@ -40,7 +40,7 @@
 weight_to_spike = 2.0
 delay = RandomDistribution("uniform", low=1, high=max_delay)
 
-loopConnections = list()
+loopConnections = []
 for i in range(0, nNeurons):
     delay_value = delay.next()
     singleConnection = (i, ((i + 1) % nNeurons), weight_to_spike, delay_value)

examples/synfire_izk_curr_exp.py

@@ -35,13 +35,13 @@
                    'i_offset': 0
                    }
 
-populations = list()
-projections = list()
+populations = []
+projections = []
 
 weight_to_spike = 30
 delay = 1
 
-loopConnections = list()
+loopConnections = []
 for i in range(0, nNeurons):
     singleConnection = ((i, (i + 1) % nNeurons, weight_to_spike, delay))
     loopConnections.append(singleConnection)

spiNNaker_start/spinnaker_start.py

@@ -93,7 +93,7 @@ def write_data_to_file(write_file, data_list):
 
 
 def read_data_from_file(read_file):
-    data_list = list()
+    data_list = []
     n_items = struct.unpack("<I", read_file.read(4))[0]
     for _ in range(n_items):
         timestamp = struct.unpack("<f", read_file.read(4))[0]
@@ -162,8 +162,8 @@ def __init__(self, x, y, connection_selector, core_counter, save, load):
         self._done = False
         self._index = 0
         self._thread = Thread(target=self._run)
-        self._p2p_active_data = list()
-        self._netinit_phase_data = list()
+        self._p2p_active_data = []
+        self._netinit_phase_data = []
         self._start_time = time.time()
         if load:
             read_file = open_file(
@@ -348,7 +348,7 @@ def __init__(
         self._save = save
         self._load = load
         self._thread = Thread(target=self._read_board)
-        self._data = list()
+        self._data = []
         self._start_time = time.time()
         if load:
             read_file = open_file(
@@ -514,8 +514,8 @@ def __init__(self, core_counter, job, save, load):
         self._thread = Thread(
             target=self.run, args=[core_counter, job, save, load])
         self._close_lock = RLock()
-        self._boot_threads = list()
-        self._processes = list()
+        self._boot_threads = []
+        self._processes = []
 
     def start(self):
         self._thread.start()
@@ -530,7 +530,7 @@ def close(self):
                 thread.close()
 
     def run(self, core_counter, job, save, load):
-        job_connections = list()
+        job_connections = []
         for (x, y), ip_address in iteritems(job.get_connections()):
             job_connections.append((x, y, ip_address))
         job_connections.sort(key=operator.itemgetter(0, 1))
@@ -541,7 +541,7 @@ def run(self, core_counter, job, save, load):
 
             # Get a list of connections to the machine and start a thread for
             # each listening for the boot to be done
-            connections = list()
+            connections = []
             root_connection = None
             boot_connection = None
             with self._close_lock:
@@ -631,7 +631,7 @@ def run(self, core_counter, job, save, load):
 
 class MockJob(object):
     def __init__(self, width, height):
-        self._boards = list()
+        self._boards = []
         self._height = height
         self._width = width
 

sudoku/set_numbers.py

@@ -186,7 +186,7 @@ def set_values(self, automatic=False):
         new_rates = get_rates(
             new_values, self._n_total, self._n_cell, self._n_N,
             int(self._default_rate.get()), int(self._max_rate.get()))
-        updated_rates = list()
+        updated_rates = []
         for i, rate in enumerate(new_rates):
             if rate != self._rates[i]:
                 updated_rates.append((i, rate))

sudoku/sudoku_main.py

@@ -193,7 +193,7 @@ def activate_visualiser(old_vis):
 # set up the cell internal inhibitory connections
 #
 print("Setting up cell inhibition...")
-connections = list()
+connections = []
 for x in range(9):
     for y in range(9):
         base = ((y * 9) + x) * n_cell

sudoku/utils.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-puzzles = list()
+puzzles = []
 puzzles.append(
     # Diabolical problem:
     [[0, 0, 1,  0, 0, 8,  0, 7, 3],