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csa_RPC.py
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csa_RPC.py
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'''
@author: Daniel Hjertholm
Tests for networks created by CSA, where both sources and targets are
drawn randomly.
'''
import numpy.random as rnd
import random
import csa
from testsuite.RPC_test import RPCTester
class CSA_RPCTester(RPCTester):
'''
Tests for networks created by CSA, where both sources and targets are
drawn randomly.
'''
def __init__(self, N_s, N_t, N, e_min=10):
'''
Construct a test object.
Parameters
----------
N_s : Number of nodes in source population.
N_t : Number of nodes in target population.
N : Total number of connections.
e_min: Minimum expected number of observations in each bin.
'''
RPCTester.__init__(self, N_s=N_s, N_t=N_t, N=N, e_min=e_min)
def _reset(self, seed):
'''
Reset the simulator and seed the PRNGs.
Parameters
----------
seed: PRNG seed value.
'''
# Set PRNG seed values:
if seed == None:
seed = rnd.randint(10 ** 10)
seed = 2 * seed # Reduces probability of overlapping seed values.
random.seed(seed) # CSA uses random.
rnd.seed(seed + 1) # _get_expected_distribution uses numpy.random.
def _build(self):
'''Create populations.'''
pass
def _connect(self):
'''Connect populations.'''
finite_set = csa.cross(xrange(self._N_s), xrange(self._N_t))
self._cs = csa.cset(csa.random(N=self._N) * finite_set)
def _degrees(self):
'''
Return list of degrees.
Parameters
----------
degree: "in" or "out".
'''
i = 0 if self._degree == 'out' else 1
connections = [c[i] for c in self._cs]
return self._counter(connections)
class InDegreeTester(CSA_RPCTester):
'''
Tests for the in-degree distribution of networks created by NEST,
where both sources and targets are drawn randomly.
'''
def __init__(self, N_s, N_t, N, e_min=10):
'''
Construct a test object.
Parameters
----------
N_s : Number of nodes in source population.
N_t : Number of nodes in target population.
N : Total number of connections.
e_min: Minimum expected number of observations in each bin.
'''
self._degree = 'in'
CSA_RPCTester.__init__(self, N_s, N_t, N, e_min)
class OutDegreeTester(CSA_RPCTester):
'''
Tests for the out-degree distribution of networks created by CSA,
where both sources and targets are drawn randomly.
'''
def __init__(self, N_s, N_t, N, e_min=10):
'''
Construct a test object.
Parameters
----------
N_s : Number of nodes in source population.
N_t : Number of nodes in target population.
N : Total number of connections.
e_min: Minimum expected number of observations in each bin.
'''
self._degree = 'out'
CSA_RPCTester.__init__(self, N_s, N_t, N, e_min)
if __name__ == '__main__':
test = InDegreeTester(N_s=100, N_t=100, N=10000)
ks, p = test.two_level_test(n_runs=100, start_seed=0)
print 'p-value of KS-test of uniformity:', p
test.show_CDF()
test.show_histogram()