def test_libcsa_cgnext(self):
"""cgnext"""
nest.ResetKernel()
w = 10000.0
d = 1.0
cs = libcsa.cset(libcsa.oneToOne, w, d)
nest.sli_push(cs)
nest.sli_run('dup')
nest.sli_push(numpy.array([0, 1, 2, 3]))
nest.sli_push(numpy.array([0, 1, 2, 3]))
nest.sli_run('cgsetmask')
nest.sli_run('dup')
nest.sli_run('cgstart')
for i in range(4):
nest.sli_run('dup')
nest.sli_run('cgnext')
self.assertEqual(nest.sli_pop(), True)
self.assertEqual(nest.sli_pop(), d)
self.assertEqual(nest.sli_pop(), w)
self.assertEqual(nest.sli_pop(), i)
self.assertEqual(nest.sli_pop(), i)
nest.sli_run('cgnext')
self.assertEqual(nest.sli_pop(), False)
def test_libcsa_cgnext(self):
"""cgnext"""
nest.ResetKernel()
w = 10000.0
d = 1.0
cs = libcsa.cset(libcsa.oneToOne, w, d)
nest.sli_push(cs)
nest.sli_run('dup')
nest.sli_push(numpy.array([0, 1, 2, 3]))
nest.sli_push(numpy.array([0, 1, 2, 3]))
nest.sli_run('cgsetmask')
nest.sli_run('dup')
nest.sli_run('cgstart')
for i in range(4):
nest.sli_run('dup')
nest.sli_run('cgnext')
self.assertEqual(nest.sli_pop(), True)
self.assertEqual(nest.sli_pop(), d)
self.assertEqual(nest.sli_pop(), w)
self.assertEqual(nest.sli_pop(), i)
self.assertEqual(nest.sli_pop(), i)
nest.sli_run('cgnext')
self.assertEqual(nest.sli_pop(), False)
def get_help_text(self, name):
nest.sli_run("statusdict /prgdocdir get")
docdir = nest.sli_pop()
helptext = "No documentation available"
for subdir in ["cc", "sli"]:
filename = os.path.join(docdir, "help", subdir, name + ".hlp")
if os.path.isfile(filename):
helptext = open(filename, 'r').read()
return helptext
def get_help_text(self, name):
nest.sli_run("statusdict /prgdocdir get")
docdir = nest.sli_pop()
helptext = "No documentation available"
for subdir in ["cc", "sli"]:
filename = os.path.join(docdir, "help", subdir, name + ".hlp")
if os.path.isfile(filename):
helptext = open(filename, 'r').read()
return helptext
def LambertWm1(x):
nest.sli_push(x)
nest.sli_run('LambertWm1')
y = nest.sli_pop()
return y
from . import compatibility
try:
import libcsa
HAVE_LIBCSA = True
except ImportError:
HAVE_LIBCSA = False
try:
import numpy
HAVE_NUMPY = True
except ImportError:
HAVE_NUMPY = False
nest.sli_run("statusdict/have_libneurosim ::")
HAVE_LIBNEUROSIM = nest.sli_pop()
@nest.check_stack
@unittest.skipIf(not HAVE_LIBCSA, 'Python libcsa package is not available')
@unittest.skipIf(
not HAVE_LIBNEUROSIM,
'PyNEST was built without the libneurosim library'
)
class libcsaTestCase(unittest.TestCase):
"""libcsa tests"""
def test_libcsa_OneToOne_subnet_1d(self):
"""One-to-one connectivity with 1-dim subnets"""
nest.ResetKernel()
def LambertWm1(x):
nest.sli_push(x); nest.sli_run('LambertWm1'); y=nest.sli_pop()
return y
print("Brunel network simulation (Python)")
print("Number of neurons : {0}".format(N_neurons))
# including devices and noise
print("Number of synapses: {0}".format(num_synapses))
# neurons + noise + spike detectors
print(
" Exitatory : {0}".format(int(CE * N_neurons) + 2 * N_neurons))
print(" Inhibitory : {0}".format(int(CI * N_neurons)))
print("Excitatory rate : %.2f Hz" % rate_ex)
print("Inhibitory rate : %.2f Hz" % rate_in)
print("Stimulus rate : %.2f Hz" % rate_stim)
print("Building time : %.2f s" % build_time)
print("Simulation time : %.2f s" % sim_time)
nest.sli_run('memory_thisjob') # virtual memory size of NEST process
memory = nest.sli_pop()
print("Memory : %.2f kB" % memory)
'''
A dictionary for population parameters is created to allow for easier access.
'''
pops = {}
pops['EX'] = {}
pops['IN'] = {}
pops['STIM'] = {}
# neuron numbers
pops['EX']['N'] = NE
pops['IN']['N'] = NI
pops['STIM']['N'] = N_stim
from . import compatibility
try:
import libcsa
HAVE_LIBCSA = True
except ImportError:
HAVE_LIBCSA = False
try:
import numpy
HAVE_NUMPY = True
except ImportError:
HAVE_NUMPY = False
nest.sli_run("statusdict/have_libneurosim ::")
HAVE_LIBNEUROSIM = nest.sli_pop()
@nest.check_stack
@unittest.skipIf(not HAVE_LIBCSA, 'Python libcsa package is not available')
@unittest.skipIf(not HAVE_LIBNEUROSIM,
'PyNEST was built without the libneurosim library')
class libcsaTestCase(unittest.TestCase):
"""libcsa tests"""
def test_libcsa_OneToOne_subnet_1d(self):
"""One-to-one connectivity with 1-dim subnets"""
nest.ResetKernel()
n = 4 # number of neurons
