def run(
attrs={
'name': 'maze',
'ind': [],
'N_e': 900,
'TS': [1],
'ff': True,
'fb': True,
'plastic': 15000
}):
so = True
print_info = attrs.get('print', True)
if print_info:
print(attrs)
sm = StorageManager(attrs, random_nr=True, print_msg=print_info)
sm.save_param_dict(attrs)
#source = LongDelayGrammar(tag='grammar_act', output_size=attrs['N_e'], random_blocks=True, mode=['simple'], input_density=0.01)
maze = Maze(level='default')
SORN = Network() #behaviour={maze.get_network_behaviour()}
SORN.maze = maze
for layer, timescale in enumerate(attrs['TS']):
e_location = NeuronGroup(
net=SORN,
tag='E_location_{}'.format(timescale),
size=maze.get_location_neuron_dimension(),
behaviour={
2:
SORN_init_neuron_vars(timescale=timescale),
3:
SORN_init_afferent_synapses(
transmitter='GLU',
density='full',
distribution='uniform(0.1,0.11)',
normalize=True,
partition_compensation=True
), # 0.89 uniform(0.1,0.11)uniform(0,[0.95#0])
4:
SORN_init_afferent_synapses(
transmitter='GABA',
density='full',
distribution='uniform(0.1,0.11)',
normalize=True
), # 0.80222 uniform(0.1,0.11) lognormal(0,[0.4#1])
9:
maze.get_location_neuron_behaviour(), ###############
12:
SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
13:
SORN_slow_syn(transmitter='GABA',
strength='-[0.1698#3]',
so=False),
17:
SORN_fast_syn(transmitter='GABA',
strength='-[0.1#4]',
so=False), # 0.11045
18:
SORN_generate_output(init_TH='0.1;+-100%'),
19:
SORN_buffer_variables(),
20:
SORN_Refractory_Analog(factor='0.5;+-50%'),
21:
SORN_STDP(eta_stdp='[0.0015#5]',
weight_attr='W_temp',
STDP_F={
-5: 0.2,
-4: 0.4,
-3: 0.6,
-2: 0.8,
-1: 1
}),
22:
SORN_temporal_synapses(syn_type='GLU',
behaviour_norm_factor=1.0),
#22: SORN_SN(syn_type='GLU', clip_max=None, behaviour_norm_factor=1.0),
23:
SORN_IP_TI(h_ip='lognormal_real_mean([0.004#6], [0.2944#7])',
eta_ip='[0.0006#8];+-50%',
integration_length='[15#18];+-50%',
clip_min=None),
25:
SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
26:
SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])',
eta_sc='[0.1#12];+-50%',
integration_length='1'), # 60;+-50% #0.05
27:
SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]'),
#29: SORN_dopamine(),
})
i_location = NeuronGroup(
net=SORN,
tag='I_location{}'.format(timescale),
size=maze.get_inhibitory_location_neuron_dimension(),
behaviour={
2:
SORN_init_neuron_vars(timescale=timescale),
3:
SORN_init_afferent_synapses(
transmitter='GLU',
density='50%',
distribution='uniform(0.1,0.11)',
normalize=True), #lognormal(0,[0.87038#14])
4:
SORN_init_afferent_synapses(
transmitter='GABA',
density='20%',
distribution='uniform(0.1,0.11)',
normalize=True), #lognormal(0,[0.82099#15])
11:
SORN_slow_syn(transmitter='GABA',
strength='-[0.1838#16]',
so=so),
14:
SORN_fast_syn(transmitter='GLU', strength='[1.5#16]',
so=so), # 1.5353
15:
SORN_fast_syn(transmitter='GABA',
strength='-[0.08#17]',
so=False), # 0.08
18:
SORN_generate_output(init_TH='0.1;+-0%'),
19:
SORN_buffer_variables(),
20:
SORN_Refractory_Analog(factor='0.2;0.7'),
})
'''
e_vision = NeuronGroup(net=SORN, tag='E_vision_{}'.format(timescale), size=maze.get_vision_neuron_dimension(), behaviour={
2: SORN_init_neuron_vars(timescale=timescale),
3: SORN_init_afferent_synapses(transmitter='GLU', density='full', distribution='lognormal(0,[0.95#0])', normalize=True, partition_compensation=True), # 0.89 uniform(0.1,0.11)
4: SORN_init_afferent_synapses(transmitter='GABA', density='45%', distribution='lognormal(0,[0.4#1])', normalize=True), # 0.80222 uniform(0.1,0.11)
9: maze.get_vision_neuron_behaviour(),
12: SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
13: SORN_slow_syn(transmitter='GABA', strength='-[0.1698#3]', so=False),
17: SORN_fast_syn(transmitter='GABA', strength='-[0.1#4]', so=False), # 0.11045
18: SORN_generate_output(init_TH='0.01'),
19: SORN_buffer_variables(),
#20: SORN_Refractory(factor='0.5;+-50%'),
#21: SORN_STDP(eta_stdp='[0.00015#5]'),
#22: SORN_SN(syn_type='GLU', clip_max=None, behaviour_norm_factor=5.0),
#23: SORN_IP_TI(h_ip='0.04', eta_ip='0.001', integration_length='[15#18];+-50%', clip_min=None),
#25: SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
#26: SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])', eta_sc='[0.1#12];+-50%',integration_length='1'), # 60;+-50% #0.05
#27: SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]')
})
'''
e_action = NeuronGroup(
net=SORN,
tag='E_action_{}'.format(timescale),
size=maze.get_action_neuron_dimension(),
behaviour={
2:
SORN_init_neuron_vars(timescale=timescale),
3:
SORN_init_afferent_synapses(
transmitter='GLU',
density='full',
distribution='uniform(0.1,0.11)',
normalize=True,
partition_compensation=True), # 0.89 lognormal(0,[0.5#0])
12:
SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
13:
SORN_slow_syn(transmitter='GABA',
strength='-[0.1698#3]',
so=False),
17:
SORN_fast_syn(transmitter='GABA',
strength='-[0.1#4]',
so=False), # 0.11045
18:
SORN_generate_output(init_TH='0.01'),
19:
SORN_buffer_variables(),
20:
SORN_Refractory_Analog(factor='0.7;+-50%'),
21:
SORN_STDP(eta_stdp='[0.0015#5]',
STDP_F={
-1: 1,
1: 0
},
weight_attr='W_temp'), #bigger #todo!!!!
#22: SORN_SN(syn_type='GLU', clip_max=None, behaviour_norm_factor=5.0),
22:
SORN_temporal_synapses(syn_type='GLU',
behaviour_norm_factor=5.0),
23:
SORN_IP_TI(h_ip='0.04',
eta_ip='0.001',
integration_length='[15#18];+-50%',
clip_min=None),
#25: SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
#26: SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])', eta_sc='[0.1#12];+-50%',integration_length='1'), # 60;+-50% #0.05
#27: SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]')
29:
SORN_dopamine(),
30:
maze.get_action_neuron_behaviour()
})
'''
e_reward = NeuronGroup(net=SORN, tag='E_reward_{}'.format(timescale), size=maze.get_reward_neuron_dimension(), behaviour={
2: SORN_init_neuron_vars(timescale=timescale),
3: SORN_init_afferent_synapses(transmitter='GLU', density='full', distribution='lognormal(0,[0.95#0])', normalize=True, partition_compensation=True),
9: maze.get_reward_neuron_behaviour(),
12: SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
18: SORN_generate_output(init_TH='0.01'),
19: SORN_buffer_variables(),
#20: SORN_Refractory(factor='0.5;+-50%'),
21: SORN_STDP(eta_stdp='[0.00015#5]'),
22: SORN_SN(syn_type='GLU', clip_max=None, behaviour_norm_factor=0.1),
#23: SORN_IP_TI(h_ip='0.04', eta_ip='0.001', integration_length='[15#18];+-50%', clip_min=None),
#25: SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
#26: SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])', eta_sc='[0.1#12];+-50%',integration_length='1'), # 60;+-50% #0.05
#27: SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]')
})
'''
e_punishment = NeuronGroup(
net=SORN,
tag='E_punishment_{}'.format(timescale),
size=maze.get_punishment_neuron_dimension(),
behaviour={
2:
SORN_init_neuron_vars(timescale=timescale),
3:
SORN_init_afferent_synapses(
transmitter='GLU',
density='full',
distribution='lognormal(0,[0.95#0])',
normalize=True,
partition_compensation=True),
9:
maze.get_punishment_neuron_behaviour(),
12:
SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
18:
SORN_generate_output(init_TH='0.01'),
19:
SORN_buffer_variables(),
#20: SORN_Refractory(factor='0.5;+-50%'),
21:
SORN_STDP(eta_stdp='[0.00015#5]'), #todo!!!!
22:
SORN_SN(syn_type='GLU',
clip_max=None,
behaviour_norm_factor=0.1),
#23: SORN_IP_TI(h_ip='0.04', eta_ip='0.001', integration_length='[15#18];+-50%', clip_min=None),
#25: SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
#26: SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])', eta_sc='[0.1#12];+-50%',integration_length='1'), # 60;+-50% #0.05
#27: SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]')
})
i_location['structure', 0].stretch_to_equal_size(e_location)
SynapseGroup(net=SORN,
src=e_location,
dst=e_location,
tag='GLU,GLU_same',
connectivity='(s_id!=d_id)*in_box(10)',
partition=True)
SynapseGroup(net=SORN,
src=e_location,
dst=i_location,
tag='GLU',
connectivity='in_box(10)',
partition=True)
SynapseGroup(net=SORN,
src=i_location,
dst=e_location,
tag='GABA',
connectivity='in_box(10)',
partition=True)
SynapseGroup(net=SORN,
src=i_location,
dst=i_location,
tag='GABA',
connectivity='(s_id!=d_id)*in_box(10)',
partition=True)
#SynapseGroup(net=SORN, src=e_vision, dst=e_location, tag='GLU', partition=True)
SynapseGroup(net=SORN,
src=e_location,
dst=e_action,
tag='GLU',
partition=True)
#SynapseGroup(net=SORN, src=e_location, dst=e_reward, tag='GLU', partition=True)
#SynapseGroup(net=SORN, src=e_reward, dst=e_location, tag='DOP+', partition=True)
#SynapseGroup(net=SORN, src=e_reward, dst=e_action, tag='DOP+', partition=True)
SynapseGroup(net=SORN,
src=e_location,
dst=e_punishment,
tag='GLU',
partition=True)
SynapseGroup(net=SORN,
src=e_punishment,
dst=e_location,
tag='DOP-',
partition=True)
SynapseGroup(net=SORN,
src=e_punishment,
dst=e_action,
tag='DOP-',
partition=True)
if __name__ == '__main__' and attrs.get('UI', False):
e_location.color = (0, 0, 255, 255)
i_location.color = (255, 0, 0, 255)
e_action.color = (255, 255, 0, 255)
#e_vision.color = (0, 255, 255, 255)
#e_reward.color = (100, 255, 100, 255)
e_punishment.color = (255, 100, 100, 255)
SORN.set_marked_variables(attrs['ind'],
info=print_info,
storage_manager=sm)
SORN.initialize(info=False)
###################################################################################################################
if __name__ == '__main__' and attrs.get('UI', False):
#default_modules.insert(0, maze_tab())
#Network_UI(SORN, label='SORN UI default setup', storage_manager=sm, group_display_count=4, reduced_layout=True).show()
Network_UI(SORN,
modules=get_default_UI_modules() + [maze_tab()],
label='SORN UI K_WTA',
storage_manager=sm,
group_display_count=1,
reduced_layout=False).show()
return 0
def run(
attrs={
'name': 'maze',
'ind': [],
'N_e': 900,
'TS': [1],
'ff': True,
'fb': True,
'plastic': 15000
}):
so = True
print_info = attrs.get('print', True)
if print_info:
print(attrs)
sm = StorageManager(attrs, random_nr=True, print_msg=print_info)
sm.save_param_dict(attrs)
#source = LongDelayGrammar(tag='grammar_act', output_size=attrs['N_e'], random_blocks=True, mode=['simple'], input_density=0.01)
maze = Maze(level='default', same_color=False)
SORN = Network() #behaviour={maze.get_network_behaviour()}
SORN.maze = maze
e_location = NeuronGroup(
net=SORN,
tag='PC_{},prediction_source'.format(1),
size=maze.get_location_neuron_dimension(),
behaviour={
2:
SORN_init_neuron_vars(timescale=1),
3:
SORN_init_afferent_synapses(
transmitter='GLU',
density='90%',
distribution='uniform(0.1,1.0)',
normalize=True
), #20%#lognormal(0,[0.95#1]) #[13#0]% #, partition_compensation=True , partition_compensation=True #lognormal(0,0.95)
#4: SORN_init_afferent_synapses(transmitter='GABA', density='[30#1]%', distribution='uniform(0.0,1.0)', normalize=True),
5:
SORN_init_afferent_synapses(transmitter='GLU_cluster',
density='90%',
distribution='uniform(0.1,1.0)',
normalize=True),
8:
maze.get_vision_neuron_behaviour(),
9:
maze.get_location_neuron_behaviour(),
#10.0: SORN_slow_syn
10.0:
SORN_slow_syn_simple(transmitter='GLU', strength='1.0',
so=so), #todo: SORN_slow_syn_simple??????
10.1:
SORN_IP_WTA_apply(),
#10.15: WTA_refrac_apply(strengthfactor='[0.1#0]'),#0.1 #attrs['refrac']
10.2:
SORN_generate_output_K_WTA_partitioned(partition_size=7,
K='[0.02#1]'),
10.3:
SORN_slow_syn_simple(transmitter='GLU_cluster', strength='1.0'),
10.4:
SORN_generate_output_K_WTA_partitioned(
partition_size=7, K='[0.02#1]', filter_temporal_output=False),
10.5:
SORN_slow_syn_simple(transmitter='GLU_cluster', strength='1.0'),
10.6:
SORN_generate_output_K_WTA_partitioned(
partition_size=7, K='[0.02#1]', filter_temporal_output=False),
10.7:
SORN_slow_syn_simple(transmitter='GLU_cluster', strength='1.0'),
10.8:
SORN_generate_output_K_WTA_partitioned(
partition_size=7, K='[0.02#1]', filter_temporal_output=False),
# 12.1: SORN_WTA_iSTDP(eta_iSTDP='[0.00015#2]'),
# 12.2: SORN_SN(syn_type='GABA'),
#13.4: SORN_generate_output_K_WTA_partitioned(K='[0.12#4]'),
#13.5: SORN_WTA_fast_syn(transmitter='GABA', strength='-[0.5#5]', so=so),#[0.1383#2]SORN_fast_syn
#14: WTA_refrac(),
#, filter_temporal_output=True
15:
SORN_buffer_variables(random_temporal_output_shift=False),
18:
WTA_refrac(decayfactor=0.5),
20:
SORN_IP_WTA(h_ip='lognormal_real_mean([0.02#1], [0.2944#2])',
eta_ip='[0.007#3]',
target_clip_min=None,
target_clip_max=None), #-1.0 #1.0 #0.007
21.1:
SORN_STDP(transmitter='GLU',
eta_stdp='[0.00015#4]',
STDP_F={
-1: 0.2,
1: -1
}), #, 0: 1 #[0.00015#7] #0.5, 0: 3.0
21.2:
SORN_STDP(transmitter='GLU_cluster',
eta_stdp='[0.00015#5]',
STDP_F={0: 2.0}), #[0.00015#7]
22:
SORN_SN(syn_type='GLU', behaviour_norm_factor=1.0),
23:
SORN_SN(syn_type='GLU_cluster',
behaviour_norm_factor='[0.3#6]'), #0.1
})
'''
e_action = NeuronGroup(net=SORN, tag='E_action_{}'.format(timescale), size=maze.get_action_neuron_dimension(), behaviour={
2: SORN_init_neuron_vars(timescale=timescale),
3: SORN_init_afferent_synapses(transmitter='GLU', density='full', distribution='uniform(0.1,0.11)', normalize=True, partition_compensation=True), # 0.89 lognormal(0,[0.5#0])
12: SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
13: SORN_slow_syn(transmitter='GABA', strength='-[0.1698#3]', so=False),
17: SORN_fast_syn(transmitter='GABA', strength='-[0.1#4]', so=False), # 0.11045
18: SORN_generate_output(init_TH='0.01'),
19: SORN_buffer_variables(),
20: SORN_Refractory_Analog(factor='0.7;+-50%'),
21: SORN_STDP(eta_stdp='[0.0015#5]', STDP_F={-1: 1, 1:0}, weight_attr='W_temp'),#bigger #todo!!!!
#22: SORN_SN(syn_type='GLU', clip_max=None, behaviour_norm_factor=5.0),
22: SORN_temporal_synapses(syn_type='GLU', behaviour_norm_factor=5.0),
23: SORN_IP_TI(h_ip='0.04', eta_ip='0.001', integration_length='[15#18];+-50%', clip_min=None),
#25: SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
#26: SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])', eta_sc='[0.1#12];+-50%',integration_length='1'), # 60;+-50% #0.05
#27: SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]')
29: SORN_dopamine(),
30: maze.get_action_neuron_behaviour()
})
29: SORN_dopamine(),
30: maze.get_action_neuron_behaviour()
'''
'''
e_reward = NeuronGroup(net=SORN, tag='E_reward_{}'.format(timescale), size=maze.get_reward_neuron_dimension(), behaviour={
2: SORN_init_neuron_vars(timescale=timescale),
3: SORN_init_afferent_synapses(transmitter='GLU', density='full', distribution='lognormal(0,[0.95#0])', normalize=True, partition_compensation=True),
9: maze.get_reward_neuron_behaviour(),
12: SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
18: SORN_generate_output(init_TH='0.01'),
19: SORN_buffer_variables(),
#20: SORN_Refractory(factor='0.5;+-50%'),
21: SORN_STDP(eta_stdp='[0.00015#5]'),
22: SORN_SN(syn_type='GLU', clip_max=None, behaviour_norm_factor=0.1),
#23: SORN_IP_TI(h_ip='0.04', eta_ip='0.001', integration_length='[15#18];+-50%', clip_min=None),
#25: SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
#26: SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])', eta_sc='[0.1#12];+-50%',integration_length='1'), # 60;+-50% #0.05
#27: SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]')
})
'''
'''
e_punishment = NeuronGroup(net=SORN, tag='E_punishment_{}'.format(timescale), size=maze.get_punishment_neuron_dimension(), behaviour={
2: SORN_init_neuron_vars(timescale=timescale),
3: SORN_init_afferent_synapses(transmitter='GLU', density='full', distribution='lognormal(0,[0.95#0])', normalize=True, partition_compensation=True),
9: maze.get_punishment_neuron_behaviour(),
12: SORN_slow_syn(transmitter='GLU', strength='[0.1383#2]', so=so),
18: SORN_generate_output(init_TH='0.01'),
19: SORN_buffer_variables(),
#20: SORN_Refractory(factor='0.5;+-50%'),
21: SORN_STDP(eta_stdp='[0.00015#5]'), #todo!!!!
22: SORN_SN(syn_type='GLU', clip_max=None, behaviour_norm_factor=0.1),
#23: SORN_IP_TI(h_ip='0.04', eta_ip='0.001', integration_length='[15#18];+-50%', clip_min=None),
#25: SORN_NOX(mp='self.partition_sum(n)', eta_nox='[0.5#9];+-50%'),
#26: SORN_SC_TI(h_sc='lognormal_real_mean([0.015#10], [0.2944#11])', eta_sc='[0.1#12];+-50%',integration_length='1'), # 60;+-50% #0.05
#27: SORN_iSTDP(h_ip='same(SCTI, th)', eta_istdp='[0.0001#13]')
})
'''
SynapseGroup(net=SORN, src=e_location, dst=e_location, tag='GLU,GLU_same')
SynapseGroup(net=SORN,
src=e_location,
dst=e_location,
tag='GLU_cluster,syn')
#SynapseGroup(net=SORN, src=e_vision, dst=e_location, tag='GLU', partition=True)
#SynapseGroup(net=SORN, src=e_location, dst=e_action, tag='GLU', partition=True)
#SynapseGroup(net=SORN, src=e_location, dst=e_reward, tag='GLU', partition=True)
#SynapseGroup(net=SORN, src=e_reward, dst=e_location, tag='DOP+', partition=True)
#SynapseGroup(net=SORN, src=e_reward, dst=e_action, tag='DOP+', partition=True)
#SynapseGroup(net=SORN, src=e_location, dst=e_punishment, tag='GLU', partition=True)
#SynapseGroup(net=SORN, src=e_punishment, dst=e_location, tag='DOP-', partition=True)
#SynapseGroup(net=SORN, src=e_punishment, dst=e_action, tag='DOP-', partition=True)
if __name__ == '__main__' and attrs.get('UI', False):
e_location.color = (0, 0, 255, 255)
#e_action.color = (255, 255, 0, 255)
#e_vision.color = (0, 255, 255, 255)
#e_reward.color = (100, 255, 100, 255)
#e_punishment.color = (255, 100, 100, 255)
SORN.set_marked_variables(attrs['ind'],
info=print_info,
storage_manager=sm)
SORN.initialize(info=False)
###################################################################################################################
if __name__ == '__main__' and attrs.get('UI', False):
#default_modules.insert(0, maze_tab())
#Network_UI(SORN, label='SORN UI default setup', storage_manager=sm, group_display_count=4, reduced_layout=True).show()
Network_UI(
SORN,
modules=get_default_UI_modules(neuron_parameters=['activity']) +
[maze_tab()],
label='SORN UI K_WTA',
storage_manager=sm,
group_display_count=1,
reduced_layout=False).show()
return 0
