id[0], len(burstsNeuron))
plt.figure()
plt.scatter(first_spike_time_for_fsi, fsi)
plt.xlabel('First spike time (ms)')
plt.ylabel('First spike time interval (ms)')
###########################################################
# calculate delivery time of the first spike in the burst #
###########################################################
(_, _, active_synapses) = reading.read_synapses(
os.path.join(dataDir, "RA_RA_active_connections_" + str(trial) + ".bin"))
(_, _, super_synapses) = reading.read_synapses(
os.path.join(dataDir, "RA_RA_super_connections_" + str(trial) + ".bin"))
(_, _, axonal_delays_RA2I) = reading.read_axonal_delays(
os.path.join(dataDir, "axonal_delays_RA2I_" + str(trial) + ".bin"))
(_, _, axonal_delays_RA2RA) = reading.read_axonal_delays(
os.path.join(dataDir, "axonal_delays_RA2RA_" + str(trial) + ".bin"))
(_, _, axonal_delays_I2RA) = reading.read_axonal_delays(
os.path.join(dataDir, "axonal_delays_I2RA_" + str(trial) + ".bin"))
nbins = 50
f = plt.figure()
ax = f.add_subplot(111)
utils.plotNormHist(
[delay for delays in axonal_delays_RA2I for delay in delays], nbins, ax,
"HVC(RA) -> HVC(I)")
utils.plotNormHist(
############# HVC-I -> HVC-RA connections #############
(_, targets_id_I2RA_before, weights_I2RA_before, \
syn_lengths_I2RA_before, axonal_delays_I2RA_before) = reading.read_connections(fileI2RABefore)
(_, targets_id_I2RA_after, weights_I2RA_after, \
syn_lengths_I2RA_after, axonal_delays_I2RA_after) = reading.read_connections(fileI2RAAfter)
############ HVC-RA -> HVC-RA connections #############
(_, _, weights_before) = reading.read_weights(fileWeightsBefore)
(_, _, weights_after) = reading.read_weights(fileWeightsAfter)
########## Axonal delays ######################
(_, _, axonal_delays_I2RA_from_delay_file_before
) = reading.read_axonal_delays(fileAxonalDelaysI2RABefore)
(_, _, axonal_delays_I2RA_from_delay_file_after
) = reading.read_axonal_delays(fileAxonalDelaysI2RAAfter)
(_, _, axonal_delays_RA2RA_from_delay_file_before
) = reading.read_axonal_delays(fileAxonalDelaysRA2RABefore)
(_, _, axonal_delays_RA2RA_from_delay_file_after
) = reading.read_axonal_delays(fileAxonalDelaysRA2RAAfter)
(_, _, axonal_delays_RA2I_from_delay_file_before
) = reading.read_axonal_delays(fileAxonalDelaysRA2IBefore)
(_, _, axonal_delays_RA2I_from_delay_file_after
) = reading.read_axonal_delays(fileAxonalDelaysRA2IAfter)
################## Activity History ###################
(_, _, activity_history_before
fileWeights = os.path.join(dirname, "weights_" + str(trial_number) + ".bin")
fileActiveSynapses = os.path.join(
dirname, "RA_RA_active_connections_" + str(trial_number) + ".bin")
fileSuperSynapses = os.path.join(
dirname, "RA_RA_super_connections_" + str(trial_number) + ".bin")
fileTraining = os.path.join(dirname, "training_neurons.bin")
fileMature = os.path.join(dirname, "mature_" + str(trial_number) + ".bin")
fileAxonalDelaysRA2RA = os.path.join(
dirname, "axonal_delays_RA2RA_" + str(trial_number) + ".bin")
#fileActive = "/home/eugene/Output/networks/chainGrowth/testGrowthDelays3/RA_RA_active_connections_5300.bin"
#(_, _, active_synapses) = reading.read_synapses(fileActive)
(_, _, axonal_delays_RA2RA) = reading.read_axonal_delays(fileAxonalDelaysRA2RA)
(_, _, active_synapses) = reading.read_synapses(fileActiveSynapses)
(_, _, super_synapses) = reading.read_synapses(fileSuperSynapses)
(_, _, weights) = reading.read_weights(fileWeights)
(_, _, mature_indicators) = reading.read_remodeled_indicators(fileMature)
training_neurons = reading.read_training_neurons(fileTraining)
print "Mature neurons: ", [
i for i in np.where(mature_indicators == 1)[0] if i not in training_neurons
]
print "Training neurons: ", training_neurons
for i in training_neurons:
print "Training neuron {0} has {1} supersynapses : {2}".format(
i, len(super_synapses[i]), super_synapses[i])