Python binomial Examples

Example #1

File: computedconnection.py Project: JoErNanO/brian

 def row_func(i):
     pyrandom.seed(initseed + int(i))
     scirandom.seed(initseed + int(i))
     k = scirandom.binomial(N, p, 1)[0]
     cur_row[:] = 0.0
     cur_row[pyrandom.sample(myrange, k)] = weight
     return cur_row

Example #2

File: constantconnection.py Project: yzerlaut/brian

 def random_matrix(self, i_start, i_end, m, offset, p):
     for i in xrange(i_start, i_end):
         k = random.binomial(m, p, 1)[0]
         r = offset + array(sample(xrange(m), k), dtype=int)
         self.rows[i] = r

Example #3

File: computedconnection.py Project: JoErNanO/brian

 def row_func(i):
     pyrandom.seed(initseed + int(i))
     scirandom.seed(initseed + int(i))
     k = scirandom.binomial(N, p, 1)[0]
     return (pyrandom.sample(myrange, k), weight)

Example #4

File: computedconstantrandomconnection.py Project: JoErNanO/brian

 def get_random_indices(self, i):
     pyrandom.seed(self.initseed + int(i))
     scirandom.seed(self.initseed + int(i))
     k = scirandom.binomial(self.m, self.p, 1)[0]
     return self.offset + array(pyrandom.sample(xrange(self.m), k), dtype=int)

Example #5

 def get_random_indices(self, i):
     pyrandom.seed(self.initseed + int(i))
     scirandom.seed(self.initseed + int(i))
     k = scirandom.binomial(self.m, self.p, 1)[0]
     return self.offset + array(pyrandom.sample(xrange(self.m), k),
                                dtype=int)

Example #6

File: computedconnection.py Project: yzerlaut/brian

 def row_func(i):
     pyrandom.seed(initseed + int(i))
     scirandom.seed(initseed + int(i))
     k = scirandom.binomial(N, p, 1)[0]
     return (pyrandom.sample(myrange, k), weight)

Example #7

File: brian_example.py Project: m0re4u/potential-spoon

P.v=-60*mV+10*mV*rand(len(P))
"""
S[0, :] = rand(N) * (Vt -
                     Vr) + Vr  # Potential: uniform between reset and threshold
"""
Connectivity matrices
---------------------
Pe=P.subgroup(3200) # excitatory group
Pi=P.subgroup(800)  # inhibitory group
Ce=Connection(Pe,P,'ge',weight=1.62*mV,sparseness=p)
Ci=Connection(Pi,P,'gi',weight=-9*mV,sparseness=p)
"""
We_target = []
We_weight = []
for _ in range(Ne):
    k = scirandom.binomial(N, p, 1)[0]
    target = sample(xrange(N), k)
    target.sort()
    We_target.append(target)
    We_weight.append([1.62 * mV] * k)
Wi_target = []
Wi_weight = []
for _ in range(Ni):
    k = scirandom.binomial(N, p, 1)[0]
    target = sample(xrange(N), k)
    target.sort()
    Wi_target.append(target)
    Wi_weight.append([-9 * mV] * k)
"""
Spike monitor
-------------

Example #8

File: simulation.py Project: beegieb/MultiArmedBandits

 def draw(self):
     """
     :return: payout with probability p, 0 with probability (1 - p)
     """
     return random.binomial(1, p=self.p) * self.payout

Example #9

File: constantconnection.py Project: JoErNanO/brian

 def random_matrix(self, i_start, i_end, m, offset, p):
     for i in xrange(i_start, i_end):
         k = random.binomial(m, p, 1)[0]
         r = offset + array(sample(xrange(m), k), dtype=int)
         self.rows[i] = r

Example #10

File: cuba_purepython.py Project: JoErNanO/brian

P.v=-60*mV+10*mV*rand(len(P))
"""
S[0, :] = rand(N) * (Vt - Vr) + Vr # Potential: uniform between reset and threshold

"""
Connectivity matrices
---------------------
Pe=P.subgroup(3200) # excitatory group
Pi=P.subgroup(800)  # inhibitory group
Ce=Connection(Pe,P,'ge',weight=1.62*mV,sparseness=p)
Ci=Connection(Pi,P,'gi',weight=-9*mV,sparseness=p)
"""
We_target = []
We_weight = []
for _ in range(Ne):
    k = scirandom.binomial(N, p, 1)[0]
    target = sample(xrange(N), k)
    target.sort()
    We_target.append(array(target))
    We_weight.append(array([1.62 * mV] * k))
Wi_target = []
Wi_weight = []
for _ in range(Ni):
    k = scirandom.binomial(N, p, 1)[0]
    target = sample(xrange(N), k)
    target.sort()
    Wi_target.append(array(target))
    Wi_weight.append(array([-9 * mV] * k))

"""
Spike monitor