def _run_microcircuit(plot_filename, conf):
import plotting
import logging
simulator = conf['simulator']
# we here only need nest as simulator, simulator = 'nest'
import pyNN.nest as sim
# prepare simulation
logging.basicConfig()
# extract parameters from config file
master_seed = conf['params_dict']['nest']['master_seed']
layers = conf['layers']
pops = conf['pops']
plot_spiking_activity = conf['plot_spiking_activity']
raster_t_min = conf['raster_t_min']
raster_t_max = conf['raster_t_max']
frac_to_plot = conf['frac_to_plot']
record_corr = conf['params_dict']['nest']['record_corr']
tau_max = conf['tau_max']
# Numbers of neurons from which to record spikes
n_rec = helper_functions.get_n_rec(conf)
sim.setup(**conf['simulator_params'][simulator])
if simulator == 'nest':
n_vp = sim.nest.GetKernelStatus('total_num_virtual_procs')
if sim.rank() == 0:
print 'n_vp: ', n_vp
print 'master_seed: ', master_seed
sim.nest.SetKernelStatus({'print_time': False,
'dict_miss_is_error': False,
'grng_seed': master_seed,
'rng_seeds': range(master_seed + 1,
master_seed + n_vp + 1),
'data_path': conf['system_params'] \
['output_path']})
import network
# result of export-files
results = []
# create network
start_netw = time.time()
n = network.Network(sim)
# contains the GIDs of the spike detectors and voltmeters needed for
# retrieving filenames later
device_list = n.setup(sim, conf)
end_netw = time.time()
if sim.rank() == 0:
print 'Creating the network took ', end_netw - start_netw, ' s'
# simulate
if sim.rank() == 0:
print "Simulating..."
start_sim = time.time()
sim.run(conf['simulator_params'][simulator]['sim_duration'])
end_sim = time.time()
if sim.rank() == 0:
print 'Simulation took ', end_sim - start_sim, ' s'
# extract filename from device_list (spikedetector/voltmeter),
# gid of neuron and thread. merge outputs from all threads
# into a single file which is then added to the task output.
for dev in device_list:
label = sim.nest.GetStatus(dev)[0]['label']
gid = sim.nest.GetStatus(dev)[0]['global_id']
# use the file extension to distinguish between spike and voltage
# output
extension = sim.nest.GetStatus(dev)[0]['file_extension']
if extension == 'gdf': # spikes
data = np.empty((0, 2))
elif extension == 'dat': # voltages
data = np.empty((0, 3))
for thread in xrange(conf['simulator_params']['nest']['threads']):
filenames = glob.glob(conf['system_params']['output_path']
+ '%s-*%d-%d.%s' % (label, gid, thread, extension))
assert(
len(filenames) == 1), 'Multiple input files found. Use a clean output directory.'
data = np.vstack([data, np.loadtxt(filenames[0])])
# delete original files
os.remove(filenames[0])
order = np.argsort(data[:, 1])
data = data[order]
outputfile_name = 'collected_%s-%d.%s' % (label, gid, extension)
outputfile = open(outputfile_name, 'w')
# the outputfile should have same format as output from NEST.
# i.e., [int, float] for spikes and [int, float, float] for voltages,
# hence we write it line by line and assign the corresponding filetype
if extension == 'gdf': # spikes
for line in data:
outputfile.write('%d\t%.3f\n' % (line[0], line[1]))
outputfile.close()
filetype = 'application/vnd.juelich.nest.spike_times'
elif extension == 'dat': # voltages
for line in data:
outputfile.write(
'%d\t%.3f\t%.3f\n' % (line[0], line[1], line[2]))
outputfile.close()
filetype = 'application/vnd.juelich.nest.analogue_signal'
res = (outputfile_name, filetype)
results.append(res)
if record_corr and simulator == 'nest':
start_corr = time.time()
if sim.nest.GetStatus(n.corr_detector, 'local')[0]:
print 'getting count_covariance on rank ', sim.rank()
cov_all = sim.nest.GetStatus(
n.corr_detector, 'count_covariance')[0]
delta_tau = sim.nest.GetStatus(n.corr_detector, 'delta_tau')[0]
cov = {}
for target_layer in np.sort(layers.keys()):
for target_pop in pops:
target_index = conf['structure'][target_layer][target_pop]
cov[target_index] = {}
for source_layer in np.sort(layers.keys()):
for source_pop in pops:
source_index = conf['structure'][
source_layer][source_pop]
cov[target_index][source_index] = \
np.array(list(
cov_all[target_index][source_index][::-1])
+ list(cov_all[source_index][target_index][1:]))
f = open(conf['system_params'][
'output_path'] + '/covariances.dat', 'w')
print >>f, 'tau_max: ', tau_max
print >>f, 'delta_tau: ', delta_tau
print >>f, 'simtime: ', conf['simulator_params'][
simulator]['sim_duration'], '\n'
for target_layer in np.sort(layers.keys()):
for target_pop in pops:
target_index = conf['structure'][target_layer][target_pop]
for source_layer in np.sort(layers.keys()):
for source_pop in pops:
source_index = conf['structure'][
source_layer][source_pop]
print >>f, target_layer, target_pop, '-', source_layer, source_pop
print >>f, 'n_events_target: ', sim.nest.GetStatus(
n.corr_detector, 'n_events')[0][target_index]
print >>f, 'n_events_source: ', sim.nest.GetStatus(
n.corr_detector, 'n_events')[0][source_index]
for i in xrange(len(cov[target_index][source_index])):
print >>f, cov[target_index][source_index][i]
print >>f, ''
f.close()
# add file covariances.dat into bundle
res_cov = ('covariances.dat',
'text/plain')
results.append(res_cov)
end_corr = time.time()
print "Writing covariances took ", end_corr - start_corr, " s"
if plot_spiking_activity and sim.rank() == 0:
plotting.plot_raster_bars(raster_t_min, raster_t_max, n_rec,
frac_to_plot, n.pops,
conf['system_params']['output_path'],
plot_filename, conf)
res_plot = (plot_filename, 'image/png')
results.append(res_plot)
sim.end()
return results
string1 = "\033[0;46m" + (message + ": ").ljust(30) + "\033[m"
string2 = "\033[1;46m" + ("%5.2f" % (time.time() - currentTimer) + " seconds").rjust(30) + "\033[m"
print(string1 + string2)
currentTimer = time.time()
def printMessage(message):
global rank
if rank == 0:
print("\033[2;46m" + (message).ljust(60) + "\033[m")
###################### MAIN BODY ###########################
## Rank for MPI ##
numberOfNodes = sim.num_processes()
rank = sim.rank()
# Log to stderr, only warnings, errors, critical
init_logging(None, num_processes=numberOfNodes, rank=rank, level=logging.WARNING)
## Start message ##
if rank == 0:
print("\033[1;45m" + (("Lattice Simulation").rjust(38)).ljust(60) + "\033[m")
print("\033[0;44m" + ("MPI_Rank: %d " % rank + " MPI_Size: %d " % numberOfNodes).ljust(60) + "\033[m")
## Timer ##
currentTimer = time.time()
totalTimer = time.time()
## Default global parameters ##
string1 = "\033[0;46m" + (message + ": ").ljust(30) + "\033[m"
string2 = "\033[1;46m" + ("%5.2f" % (time.time() - currentTimer) + " seconds").rjust(30) + "\033[m"
print(string1 + string2)
currentTimer = time.time()
def printMessage(message):
global rank
if rank==0:
print("\033[2;46m" + (message).ljust(60) + "\033[m")
###################### MAIN BODY ###########################
## Rank for MPI ##
global numberOfNodes, rank
numberOfNodes = sim.num_processes()
rank = sim.rank()
# Log to stderr, only warnings, errors, critical
init_logging('sim.log',num_processes=numberOfNodes,rank=rank,level=logging.DEBUG)
## Start message ##
if rank==0:
print("\033[1;45m" + (("Lattice Simulation").rjust(38)).ljust(60) + "\033[m")
print("\033[0;44m" + ("MPI_Rank: %d " % rank + " MPI_Size: %d " % numberOfNodes).ljust(60) + "\033[m")
## Timer ##
global currentTimer, totalTimer
currentTimer = time.time()
totalTimer = time.time()
def _run_microcircuit(plot_filename, conf):
import plotting
import logging
simulator = conf['simulator']
# we here only need nest as simulator, simulator = 'nest'
import pyNN.nest as sim
# prepare simulation
logging.basicConfig()
# extract parameters from config file
master_seed = conf['params_dict']['nest']['master_seed']
layers = conf['layers']
pops = conf['pops']
plot_spiking_activity = conf['plot_spiking_activity']
raster_t_min = conf['raster_t_min']
raster_t_max = conf['raster_t_max']
frac_to_plot = conf['frac_to_plot']
record_corr = conf['params_dict']['nest']['record_corr']
tau_max = conf['tau_max']
# Numbers of neurons from which to record spikes
n_rec = helper_functions.get_n_rec(conf)
sim.setup(**conf['simulator_params'][simulator])
if simulator == 'nest':
n_vp = sim.nest.GetKernelStatus('total_num_virtual_procs')
if sim.rank() == 0:
print 'n_vp: ', n_vp
print 'master_seed: ', master_seed
sim.nest.SetKernelStatus({'print_time': False,
'dict_miss_is_error': False,
'grng_seed': master_seed,
'rng_seeds': range(master_seed + 1,
master_seed + n_vp + 1),
# PYTHON2.6: FOR WRITING OUTPUT FROM
# RECORDING DEVICES WITH PYNEST FUNCTIONS,
# THE OUTPUT PATH IS NOT AUTOMATICALLY THE
# CWD BUT HAS TO BE SET MANUALLY
'data_path': conf['system_params']['output_path']})
import network
# result of export-files
results = []
# create network
start_netw = time.time()
n = network.Network(sim)
# PYTHON2.6: device_list CONTAINS THE GIDs OF THE SPIKE DETECTORS AND VOLTMETERS
# NEEDED FOR RETRIEVING FILENAMES LATER
device_list = n.setup(sim, conf)
end_netw = time.time()
if sim.rank() == 0:
print 'Creating the network took ', end_netw - start_netw, ' s'
# simulate
if sim.rank() == 0:
print "Simulating..."
start_sim = time.time()
sim.run(conf['simulator_params'][simulator]['sim_duration'])
end_sim = time.time()
if sim.rank() == 0:
print 'Simulation took ', end_sim - start_sim, ' s'
# extract filename from device_list (spikedetector/voltmeter),
# gid of neuron and thread. merge outputs from all threads
# into a single file which is then added to the task output.
# PYTHON2.6: NEEDS TO BE ADAPTED IF NOT RECORDED VIA PYNEST
for dev in device_list:
label = sim.nest.GetStatus(dev)[0]['label']
gid = sim.nest.GetStatus(dev)[0]['global_id']
# use the file extension to distinguish between spike and voltage output
extension = sim.nest.GetStatus(dev)[0]['file_extension']
if extension == 'gdf': # spikes
data = np.empty((0, 2))
elif extension == 'dat': # voltages
data = np.empty((0, 3))
for thread in xrange(conf['simulator_params']['nest']['threads']):
filenames = glob.glob(conf['system_params']['output_path']
+ '%s-*%d-%d.%s' % (label, gid, thread, extension))
assert(len(filenames) == 1), 'Multiple input files found. Use a clean output directory.'
data = np.vstack([data, np.loadtxt(filenames[0])])
# delete original files
os.remove(filenames[0])
order = np.argsort(data[:, 1])
data = data[order]
outputfile_name = 'collected_%s-%d.%s' % (label, gid, extension)
outputfile = open(outputfile_name, 'w')
# the outputfile should have same format as output from NEST.
# i.e., [int, float] for spikes and [int, float, float] for voltages,
# hence we write it line by line and assign the corresponding filetype
if extension == 'gdf': # spikes
for line in data:
outputfile.write('%d\t%.3f\n' % (line[0], line[1]))
outputfile.close()
filetype = 'application/vnd.juelich.nest.spike_times'
elif extension == 'dat': # voltages
for line in data:
outputfile.write('%d\t%.3f\t%.3f\n' % (line[0], line[1], line[2]))
outputfile.close()
filetype = 'application/vnd.juelich.nest.analogue_signal'
res = (outputfile_name, filetype)
results.append(res)
# start_writing = time.time()
# PYTHON2.6: SPIKE AND VOLTAGE FILES ARE CURRENTLY WRITTEN WHEN A SPIKE
# DETECTOR OR A VOLTMETER IS CONNECTED WITH 'to_file': True
# for layer in layers:
# for pop in pops:
# # filename = conf['system_params']['output_path'] + '/spikes_' + layer + pop + '.dat'
# filename = conf['system_params']['output_path'] + 'spikes_' + layer + pop + '.dat'
# n.pops[layer][pop].printSpikes(filename, gather=False)
# # add filename and filepath into results
# subres = (filename, 'application/vnd.juelich.bundle.nest.data')
# results.append(subres)
# if record_v:
# for layer in layers:
# for pop in pops:
# filename = conf['system_params']['output_path'] + '/voltages_' + layer + pop + '.dat'
# n.pops[layer][pop].print_v(filename, gather=False)
if record_corr and simulator == 'nest':
start_corr = time.time()
if sim.nest.GetStatus(n.corr_detector, 'local')[0]:
print 'getting count_covariance on rank ', sim.rank()
cov_all = sim.nest.GetStatus(n.corr_detector, 'count_covariance')[0]
delta_tau = sim.nest.GetStatus(n.corr_detector, 'delta_tau')[0]
cov = {}
for target_layer in np.sort(layers.keys()):
for target_pop in pops:
target_index = conf['structure'][target_layer][target_pop]
cov[target_index] = {}
for source_layer in np.sort(layers.keys()):
for source_pop in pops:
source_index = conf['structure'][source_layer][source_pop]
cov[target_index][source_index] = np.array(list(cov_all[target_index][source_index][::-1])
+ list(cov_all[source_index][target_index][1:]))
f = open(conf['system_params']['output_path'] + '/covariances.dat', 'w')
print >>f, 'tau_max: ', tau_max
print >>f, 'delta_tau: ', delta_tau
print >>f, 'simtime: ', conf['simulator_params'][simulator]['sim_duration'], '\n'
for target_layer in np.sort(layers.keys()):
for target_pop in pops:
target_index = conf['structure'][target_layer][target_pop]
for source_layer in np.sort(layers.keys()):
for source_pop in pops:
source_index = conf['structure'][source_layer][source_pop]
print >>f, target_layer, target_pop, '-', source_layer, source_pop
print >>f, 'n_events_target: ', sim.nest.GetStatus(n.corr_detector, 'n_events')[0][target_index]
print >>f, 'n_events_source: ', sim.nest.GetStatus(n.corr_detector, 'n_events')[0][source_index]
for i in xrange(len(cov[target_index][source_index])):
print >>f, cov[target_index][source_index][i]
print >>f, ''
f.close()
# add file covariances.dat into bundle
res_cov = ('covariances.dat',
'text/plain')
results.append(res_cov)
end_corr = time.time()
print "Writing covariances took ", end_corr - start_corr, " s"
# end_writing = time.time()
# print "Writing data took ", end_writing - start_writing, " s"
if plot_spiking_activity and sim.rank() == 0:
plotting.plot_raster_bars(raster_t_min, raster_t_max, n_rec,
frac_to_plot, n.pops,
conf['system_params']['output_path'],
plot_filename, conf)
res_plot = (plot_filename, 'image/png')
results.append(res_plot)
sim.end()
return results