Each population has 256 neurons (4 neurons x 64 channels). Neurons in each population (ear) are numbered from 0 to 255, where:: id = ( channel * 4 ) + neuron .. moduleauthor:: Francesco Galluppi, SpiNNaker Project, [email protected] """ from pyNN.utility import get_script_args from pyNN.errors import RecordingError import pyNN.spiNNaker as p p.setup(timestep=1.0,min_delay=1.0,max_delay=10.0, db_name='cochlea_example.sqlite') nNeurons = 4 * 64 # 4 neurons and 64 channels per ear p.get_db().set_number_of_neurons_per_core('IF_curr_exp', nNeurons) # this will set 256 neurons per core cell_params = { 'i_offset' : .1, 'tau_refrac' : 3.0, 'v_rest' : -65.0, 'v_thresh' : -51.0, 'tau_syn_E' : 2.0, 'tau_syn_I': 5.0, 'v_reset' : -70.0, 'e_rev_E' : 0., 'e_rev_I' : -80.} left_cochlea_ear = p.Population(nNeurons, p.ProxyNeuron, {'x_source':254, 'y_source':254}, label='left_cochlea_ear') left_cochlea_ear.set_mapping_constraint({'x':0, 'y':0}) left_cochlea_ear.record() # this should record spikes from the cochlea right_cochlea_ear = p.Population(nNeurons, p.SpikeSource, {}, label='right_cochlea_ear') right_cochlea_ear = p.Population(nNeurons, p.ProxyNeuron, {'x_source':254, 'y_source':255}, label='left_cochlea_ear') right_cochlea_ear.set_mapping_constraint({'x':0, 'y':0})
LOGLEVEL = LOGINFO
#### DEFAULTS
tau_syn = 100 # default value
neurons_per_core = 100 # default value
#### COUNTERS
n_outs = 0 # output counter for placing NEF_out populations in chip 0,0
# Setting up the connection with the DB and the number of cells
spinn.setup(db_name = os.path.abspath('%s/nengo_model.sqlite' % pacman.BINARIES_DIRECTORY))
spinn.get_db().set_number_of_neurons_per_core('NEF_out_2d', neurons_per_core*2) # this will set one population per core
#spinn.get_db().set_number_of_neurons_per_core('IF_curr_exp_32', neurons_per_core) # this will set one population per core
spinn.get_db().set_number_of_neurons_per_core('IF_NEF_input_2d', neurons_per_core*2) # this will set one population per core
# PACMAN INTERFACES
class general_cell():
"""
PACMAN Interface class giving a cell type with parameters, class, size, label, id and mapping constraints
"""
def __init__(self, cellname):
self.__name__ = cellname
class population_interface():
"""
Synfirechain-like example
Expected results in
.. figure:: ./examples/results/synfire_chain_lif.png
"""
#!/usr/bin/python
import pyNN.spiNNaker as p
import numpy, pylab
p.setup(timestep=1.0, min_delay=1.0, max_delay=8.0, db_name='synfire.sqlite')
n_pop = 16 # number of populations
nNeurons = 10 # number of neurons in each population
p.get_db().set_number_of_neurons_per_core(
'IF_curr_exp', nNeurons) # this will set one population per core
# random distributions
rng = p.NumpyRNG(seed=28374)
delay_distr = p.RandomDistribution('uniform', [1, 10], rng=rng)
weight_distr = p.RandomDistribution('uniform', [0, 2], rng=rng)
v_distr = p.RandomDistribution('uniform', [-55, -95], rng)
cell_params_lif_in = {
'tau_m': 32,
'v_init': -80,
'v_rest': -75,
'v_reset': -95,
'v_thresh': -55,
'tau_syn_E': 5,
'tau_syn_I': 10,
Expected results in
.. figure:: ./examples/results/synfire_chain_lif.png
"""
#!/usr/bin/python
import pyNN.spiNNaker as p
import numpy, pylab
p.setup(timestep=1.0, min_delay = 1.0, max_delay = 8.0, db_name='synfire.sqlite')
n_pop = 16 # number of populations
nNeurons = 10 # number of neurons in each population
p.get_db().set_number_of_neurons_per_core('IF_curr_exp', nNeurons) # this will set one population per core
# random distributions
rng = p.NumpyRNG(seed=28374)
delay_distr = p.RandomDistribution('uniform', [1,10], rng=rng)
weight_distr = p.RandomDistribution('uniform', [0,2], rng=rng)
v_distr = p.RandomDistribution('uniform', [-55,-95], rng)
cell_params_lif_in = { 'tau_m' : 32,
'v_init' : -80,
'v_rest' : -75,
'v_reset' : -95,
'v_thresh' : -55,
'tau_syn_E' : 5,
'tau_syn_I' : 10,
id = ( channel * 4 ) + neuron .. moduleauthor:: Francesco Galluppi, SpiNNaker Project, [email protected] """ from pyNN.utility import get_script_args from pyNN.errors import RecordingError import pyNN.spiNNaker as p p.setup(timestep=1.0, min_delay=1.0, max_delay=10.0, db_name='cochlea_example.sqlite') nNeurons = 4 * 64 # 4 neurons and 64 channels per ear p.get_db().set_number_of_neurons_per_core( 'IF_curr_exp', nNeurons) # this will set 256 neurons per core cell_params = { 'i_offset': .1, 'tau_refrac': 3.0, 'v_rest': -65.0, 'v_thresh': -51.0, 'tau_syn_E': 2.0, 'tau_syn_I': 5.0, 'v_reset': -70.0, 'e_rev_E': 0., 'e_rev_I': -80. } left_cochlea_ear = p.Population(nNeurons, p.ProxyNeuron, {