Merge pull request #125 from SpiNNakerManchester/PopulationVertex

SpliiterPopulationVertex refactor

Author: Christian-B

balanced_random/split/balanced_random_split.py

@@ -18,7 +18,7 @@
 from pyNN.utility.plotting import Figure, Panel
 import pyNN.spiNNaker as p
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterPoissonDelegate, SplitterAbstractPopulationVertexNeuronsSynapses)
+    SplitterPoissonDelegate, SplitterPopulationVertexNeuronsSynapses)
 
 p.setup(timestep=0.1, time_scale_factor=1)
 p.set_number_of_neurons_per_core(p.IF_curr_exp, 64)
@@ -39,12 +39,12 @@
                          label="Input")
 
 pop_exc_splitter = \
-    SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+    SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 pop_exc = p.Population(n_exc, p.IF_curr_exp, label="Excitatory",
                        additional_parameters={"splitter": pop_exc_splitter,
                                               "seed": 1})
 pop_inh_splitter = \
-    SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+    SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 pop_inh = p.Population(n_inh, p.IF_curr_exp, label="Inhibitory",
                        additional_parameters={"splitter": pop_inh_splitter,
                                               "seed": 2})

examples/partitioner_examples/splitter_usage.py

@@ -18,7 +18,7 @@
     SplitterOneToOneLegacy as OneToOneSplitter,
     SplitterFixedLegacy)
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexFixed)
+    SplitterPopulationVertexFixed)
 
 runtime = 1000
 n_neurons = 100  # number of neurons in each population
@@ -31,20 +31,20 @@
 neuron = p.Population(
     n_neurons, p.IF_curr_exp(), label='pop_1',
     additional_parameters={
-        "splitter_object": SplitterAbstractPopulationVertexFixed()})
+        "splitter_object": SplitterPopulationVertexFixed()})
 neuron.record("all")
 neuron2 = p.Population(
     int(n_neurons / 2), p.IF_curr_exp(), label='pop_1',
     additional_parameters={
-        "splitter_object": SplitterAbstractPopulationVertexFixed()})
+        "splitter_object": SplitterPopulationVertexFixed()})
 neuron3 = p.Population(
     n_neurons * 2, p.IF_curr_exp(), label='pop_1',
     additional_parameters={
-        "splitter_object": SplitterAbstractPopulationVertexFixed()})
+        "splitter_object": SplitterPopulationVertexFixed()})
 neuron4 = p.Population(
     int(n_neurons / 3), p.IF_curr_exp(), label='pop_1',
     additional_parameters={
-        "splitter_object": SplitterAbstractPopulationVertexFixed()})
+        "splitter_object": SplitterPopulationVertexFixed()})
 input1 = p.Population(
     n_neurons, p.SpikeSourcePoisson(), label='inputSpikes_1',
     additional_parameters={

examples/split_examples/pynnBrunnelSplit.py

@@ -19,7 +19,7 @@
 from pyNN.random import RandomDistribution
 from pyNN.utility.plotting import Figure, Panel
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
+    SplitterPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
 
 simulator_Name = 'spiNNaker'
 # exec('import pyNN.%s as pynn' % simulator_Name)
@@ -164,12 +164,12 @@ def poisson_generator(rate, rng, t_start=0.0, t_stop=1000.0, array=True,
 }
 
 # Set-up pynn Populations
-E_pop_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(3, 128, False)
+E_pop_splitter = SplitterPopulationVertexNeuronsSynapses(3, 128, False)
 E_pop = pynn.Population(
     N_E, pynn.IF_curr_exp(**exc_cell_params), label="E_pop",
     additional_parameters={"splitter": E_pop_splitter}, seed=1)
 
-I_pop_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(3, 128, False)
+I_pop_splitter = SplitterPopulationVertexNeuronsSynapses(3, 128, False)
 I_pop = pynn.Population(
     N_I, pynn.IF_curr_exp(**inh_cell_params), label="I_pop",
     additional_parameters={"splitter": I_pop_splitter}, seed=2)

examples/split_examples/stdp_neuromodulated_example_split.py

@@ -27,7 +27,7 @@
 """
 
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexNeuronsSynapses)
+    SplitterPopulationVertexNeuronsSynapses)
 
 import pyNN.spiNNaker as sim
 import pylab
@@ -87,7 +87,7 @@
 for i in range(n_pops):
     stimulation.append(sim.Population(n_neurons, sim.SpikeSourcePoisson,
                        {'rate': stim_rate, 'duration': duration}, label="pre"))
-    post_splitters.append(SplitterAbstractPopulationVertexNeuronsSynapses(2))
+    post_splitters.append(SplitterPopulationVertexNeuronsSynapses(2))
     post_pops.append(sim.Population(
         n_neurons, sim.IF_curr_exp, cell_params, label='post',
         additional_parameters={"splitter": post_splitters[i]}))

examples/split_examples/structural_plasticity_with_stdp_neuromodulated.py

@@ -32,7 +32,7 @@
 """
 
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexNeuronsSynapses)
+    SplitterPopulationVertexNeuronsSynapses)
 
 import pyNN.spiNNaker as sim
 import pylab
@@ -120,7 +120,7 @@
 for i in range(n_pops):
     stimulation.append(sim.Population(n_neurons, sim.SpikeSourcePoisson,
                        {'rate': stim_rate, 'duration': duration}, label="pre"))
-    post_splitters.append(SplitterAbstractPopulationVertexNeuronsSynapses(1))
+    post_splitters.append(SplitterPopulationVertexNeuronsSynapses(1))
     post_pops.append(sim.Population(
         n_neurons, sim.IF_curr_exp, cell_params, label='post',
         additional_parameters={"splitter": post_splitters[i]}))

examples/split_examples/va_benchmark_split.py

@@ -33,7 +33,7 @@
 from pyNN.utility.plotting import Figure, Panel
 import matplotlib.pyplot as plt
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexNeuronsSynapses)
+    SplitterPopulationVertexNeuronsSynapses)
 
 
 simulator_name = 'spiNNaker'
@@ -158,11 +158,11 @@
 timer.start()
 
 print("%s Creating cell populations..." % node_id)
-exc_cells_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(2)
+exc_cells_splitter = SplitterPopulationVertexNeuronsSynapses(2)
 exc_cells = p.Population(
     n_exc, celltype(**cell_params), label="Excitatory_Cells",
     additional_parameters={"splitter": exc_cells_splitter}, seed=1)
-inh_cells_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(3)
+inh_cells_splitter = SplitterPopulationVertexNeuronsSynapses(3)
 inh_cells = p.Population(
     n_inh, celltype(**cell_params), label="Inhibitory_Cells",
     additional_parameters={"splitter": inh_cells_splitter}, seed=2)

learning/split/stdp_split.py

@@ -16,19 +16,19 @@
 import matplotlib.pyplot as plt
 import pyNN.spiNNaker as sim
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
+    SplitterPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
 
 n_neurons = 192
 simtime = 5000
 
 sim.setup(timestep=1.0)
 sim.set_number_of_neurons_per_core(sim.IF_curr_exp, 64)
 
-pre_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+pre_splitter = SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 pre_pop = sim.Population(
     n_neurons, sim.IF_curr_exp(), label="Pre", additional_parameters={
         "splitter": pre_splitter})
-post_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+post_splitter = SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 post_pop = sim.Population(
     n_neurons, sim.IF_curr_exp(), label="Post", additional_parameters={
         "splitter": post_splitter})

learning/split/struct_pl_split.py

@@ -17,18 +17,18 @@
 import pyNN.utility.plotting as plot
 import pyNN.spiNNaker as sim
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
+    SplitterPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
 
 n_neurons = 64
 simtime = 5000
 
 sim.setup(timestep=1.0)
 
-pre_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+pre_splitter = SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 pre_pop = sim.Population(
     n_neurons, sim.IF_curr_exp(), label="Pre", additional_parameters={
         "splitter": pre_splitter})
-post_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+post_splitter = SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 post_pop = sim.Population(
     n_neurons, sim.IF_curr_exp(), label="Post", additional_parameters={
         "splitter": post_splitter})

learning/split/struct_pl_stdp_split.py

@@ -17,19 +17,19 @@
 import pyNN.spiNNaker as sim
 import pyNN.utility.plotting as plot
 from spynnaker.pyNN.extra_algorithms.splitter_components import (
-    SplitterAbstractPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
+    SplitterPopulationVertexNeuronsSynapses, SplitterPoissonDelegate)
 
 n_neurons = 192
 simtime = 5000
 
 sim.setup(timestep=1.0)
 
 sim.set_number_of_neurons_per_core(sim.IF_curr_exp, 64)
-pre_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+pre_splitter = SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 pre_pop = sim.Population(
     n_neurons, sim.IF_curr_exp(), label="Pre", additional_parameters={
         "splitter": pre_splitter})
-post_splitter = SplitterAbstractPopulationVertexNeuronsSynapses(1, 128, False)
+post_splitter = SplitterPopulationVertexNeuronsSynapses(1, 128, False)
 post_pop = sim.Population(
     n_neurons, sim.IF_curr_exp(), label="Post", additional_parameters={
         "splitter": post_splitter})