network_dir, "RA_RA_active_connections_" + str(trial_number) + ".bin")
fileAxonalDelaysRA2RA = os.path.join(
network_dir, "axonal_delays_RA2RA_" + str(trial_number) + ".bin")
fileSpikeTimes = "/home/eugene/Output/networks/chainGrowth/matureTest/test_spike_times_soma_2.bin"
#MARGIN_LATE = 0.5 # margin for the burst coming late
MARGIN_LATE = 0.0 # margin for the burst coming late
(N_RA, _, mature_indicators) = reading.read_mature_indicators(fileMature)
(_, _, active_synapses) = reading.read_synapses(fileActiveSynapses)
(_, _, axonal_delays_RA2RA) = reading.read_axonal_delays(fileAxonalDelaysRA2RA)
print "Number of HVC(RA) neurons = ", N_RA
(_, _, spike_times_soma,
neuron_fired_soma) = reading.read_time_info(fileSpikeTimes)
#print "Dedritic spikes: ", neuron_fired_dend
#print "Dendritic spike times: ", spike_times_dend
#print "Somatic spikes: ", neuron_fired_soma
#print "Somatic spike times: ", spike_times_soma
#print ordered_soma_spikes_raw
#print ordered_soma_raw
first_spike_times = np.empty(N_RA, np.float32)
first_spike_times.fill(-1.0)
for n, time in zip(neuron_fired_soma, spike_times_soma):
first_spike_times[n] = time[0]
def write_pajek_network_subset(dirname, trial_number, N, fileSpikes):
"""
Create .net file with locations and connections between mature HVC-RA neurons in array
first N mature neurons that spiked are plotted
"""
file_RA_xy = os.path.join(dirname, "RA_xy_" + str(trial_number) + ".bin")
file_training = os.path.join(dirname, "training_neurons.bin")
file_pajek = os.path.join(dirname,
"network_subset_" + str(trial_number) + ".net")
fileMature = os.path.join(dirname, "mature_" + str(trial_number) + ".bin")
fileSuperSynapses = os.path.join(
dirname, "RA_RA_super_connections_" + str(trial_number) + ".bin")
fileWeights = os.path.join(dirname,
"weights_" + str(trial_number) + ".bin")
coord_RA = reading.read_coordinates(file_RA_xy)
training_neurons = reading.read_training_neurons(file_training)
(N_RA, _, weights) = reading.read_weights(fileWeights)
(_, _, mature_indicators) = reading.read_mature_indicators(fileMature)
(_, _, super_synapses) = reading.read_synapses(fileSuperSynapses)
#print list(mature_neurons)
#mature_neurons = range(N_RA)
# sort array with neurons and training neurons #
training_neurons.sort()
#fileDend = "/home/eugene/Output/networks/chainGrowth/passiveDendrite/test/noImmatureOut4/test_spike_times_dend_5.bin"
#fileSoma = "/home/eugene/Output/networks/chainGrowth/passiveDendrite/test/noImmatureOut4/test_spike_times_soma_5.bin"
(_, _, spike_times_soma,
neuron_fired_soma) = reading.read_time_info(fileSpikes)
ordered_soma_spikes_raw, ordered_soma_raw = zip(
*sorted(zip(spike_times_soma, neuron_fired_soma)))
first_mature_spiked = []
for spikes, neuron_ids in zip(ordered_soma_spikes_raw, ordered_soma_raw):
if len(first_mature_spiked) >= N:
break
if mature_indicators[neuron_ids[0]] == 1:
first_mature_spiked.append(neuron_ids[0])
first_mature_spiked.sort()
num_neurons = len(first_mature_spiked)
with open(file_pajek, 'w') as f:
f.write("*Vertices {0}\n".format(num_neurons))
for i, neuron_id in enumerate(first_mature_spiked):
if neuron_id in training_neurons:
f.write('{0} "{1}" {2} {3} {4} ic Green\n'.format(
i + 1, neuron_id, coord_RA[neuron_id][0],
coord_RA[neuron_id][1], coord_RA[neuron_id][2]))
else:
f.write('{0} "{1}" {2} {3} {4} ic Yellow\n'.format(
i + 1, neuron_id, coord_RA[neuron_id][0],
coord_RA[neuron_id][1], coord_RA[neuron_id][2]))
f.write("*Arcs\n".format(num_neurons))
# write targets of HVC(RA) neurons
for i, source_id in enumerate(first_mature_spiked):
for target_id in super_synapses[source_id]:
try:
ind = utils.index(first_mature_spiked, target_id)
f.write('{0} {1} {2} c Green\n'.format(
i + 1, ind + 1, weights[source_id][target_id]))
except ValueError:
continue
#fileSpikeTimes = os.path.join(dirname, "spike_times_soma_" + str(trial_number) + ".bin")
fileDelaysRA2RA = os.path.join(
dirname, "axonal_delays_RA2RA_" + str(trial_number) + ".bin")
fileMature = os.path.join(dirname, "mature_" + str(trial_number) + ".bin")
fileWeights = os.path.join(dirname, "weights_" + str(trial_number) + ".bin")
fileTraining = os.path.join(dirname, "training_neurons.bin")
#fileSpikeTimes = "/home/eugene/Output/networks/chainGrowth/passiveDendrite/test/maturationTransition4/test_spike_times_soma_7.bin"
#fileSpikeTimes = "/home/eugene/results/immature/clusters/test/matTrans44/test_spike_times_soma_10.bin"
fileSpikeTimes = "/mnt/hodgkin/eugene/results/immature/clusters/matTrans54/spike_times_soma_13400.bin"
MARGIN_LATE = 0.0 # margin for the burst coming late
(N_RA, _, active_synapses) = reading.read_synapses(fileConnections)
(_, _, spike_times_raw, neuron_spiked) = reading.read_time_info(fileSpikeTimes)
(_, _, axonal_delays_RA2RA) = reading.read_axonal_delays(fileDelaysRA2RA)
(_, _, weights) = reading.read_weights(fileWeights)
(_, _, mature_indicators) = reading.read_mature_indicators(fileMature)
training_neurons = reading.read_training_neurons(fileTraining)
print "Number of HVC(RA) neurons = ", N_RA
first_spike_times = np.empty(N_RA, np.float32)
first_spike_times.fill(-1.0)
for n, time in zip(neuron_spiked, spike_times_raw):
first_spike_times[n[0]] = time[0]
delivered_times_and_id = []
arrivals = []
#dirname = "/home/eugene/Output/networks/chainGrowth/passiveDendrite/maturationTransition4/"
dirname = "/mnt/hodgkin/eugene/results/immature/clusters/matTrans62/"
trial_number = 32400
fileCoordRA = os.path.join(dirname, "RA_xy_" + str(trial_number) + ".bin")
fileTraining = os.path.join(dirname, "training_neurons.bin")
#fileSoma = os.path.join(dirname, "spike_times_soma_" + str(trial_number) + ".bin")
#fileSoma = "/home/eugene/Output/networks/chainGrowth/passiveDendrite/test/noImmatureOut8/test_spike_times_soma_5.bin"
fileSoma = "/mnt/hodgkin/eugene/results/immature/clusters/test/matTrans62/trial32400/test_spike_times_soma_5.bin"
coord = reading.read_coordinates(fileCoordRA)
training_neurons = reading.read_training_neurons(fileTraining)
(_, _, mature_indicators) = reading.read_mature_indicators(os.path.join(dirname, "mature_"+str(trial_number)+".bin"))
(_, _, spike_times_soma, neuron_fired_soma) = reading.read_time_info(fileSoma)
print "Number of spiked neurons: ",len(spike_times_soma)
for spikes, neuron_id in zip(spike_times_soma, neuron_fired_soma):
if len(spikes) > 6:
print "Neuron {0} produced {1} spikes".format(neuron_id[0], len(spikes))
#print "Dedritic spikes: ", neuron_fired_dend
#print "Dendritic spike times: ", spike_times_dend
#print "Somatic spikes: ", neuron_fired_soma
#print "Somatic spike times: ", spike_times_soma
#print ordered_soma_spikes_raw
#print ordered_soma_raw
# # i = 0 # while i < len(neurons_in_chain): # if len(super_synapses[neurons_in_chain[i]]) > 0: # for j in super_synapses[neurons_in_chain[i]]: # if j not in neurons_in_chain: # neurons_in_chain.append(j) # # i += 1 # #============================================================================== print "Neurons in chain: ",neurons_in_chain (trial_number, simulation_time, spike_times_soma, neuron_fired_soma) = reading.read_time_info(fileSoma) set_neurons_in_chain = set(neurons_in_chain) #print "Dedritic spikes: ", neuron_fired_dend #print "Dendritic spike times: ", spike_times_dend #print "Somatic spikes: ", neuron_fired_soma #print "Somatic spike times: ", spike_times_soma #################################### ### Order neurons by their first spike time #################################### ordered_soma_spikes_raw, ordered_soma_raw = zip(*sorted(zip(spike_times_soma, neuron_fired_soma))) #print ordered_soma_spikes_raw
import numpy as np fileDend_noDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthNoDelays/spike_times_dend.bin" fileSoma_noDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthNoDelays/spike_times_soma.bin" fileInterneuron_noDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthNoDelays/spike_times_interneuron.bin" fileWeights_noDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthNoDelays/weights_10.bin" fileActiveSynapses_noDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthNoDelays/RA_RA_active_connections.bin" fileDend_zeroDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthDelays/spike_times_dend.bin" fileSoma_zeroDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthDelays/spike_times_soma.bin" fileInterneuron_zeroDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthDelays/spike_times_interneuron.bin" fileWeights_zeroDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthDelays/weights_10.bin" fileActiveSynapses_zeroDelays = "/home/eugene/Output/networks/chainGrowth/testGrowthDelays/RA_RA_active_connections.bin" (_, _, spike_times_dend_noDelays, neuron_fired_dend_noDelays) = reading.read_time_info(fileDend_noDelays) (_, _, spike_times_soma_noDelays, neuron_fired_soma_noDelays) = reading.read_time_info(fileSoma_noDelays) (_, _, spike_times_interneuron_noDelays, interneuron_fired_noDelays) = reading.read_time_info(fileInterneuron_noDelays) (_, _, spike_times_dend_zeroDelays, neuron_fired_dend_zeroDelays) = reading.read_time_info(fileDend_zeroDelays) (_, _, spike_times_soma_zeroDelays, neuron_fired_soma_zeroDelays) = reading.read_time_info(fileSoma_zeroDelays) (_, _, spike_times_interneuron_zeroDelays, interneuron_fired_zeroDelays ) = reading.read_time_info(fileInterneuron_zeroDelays) (_, _, weights_noDelays) = reading.read_weights(fileWeights_noDelays) (_, _, weights_zeroDelays) = reading.read_weights(fileWeights_zeroDelays)