In [8]:

    




    

In [23]:

    

d = 400
T = 100
x = zeros((d,T))
y = zeros((d,T))

a = 0.5
tauPsi = 1.
tauRho = 1.
tauPhi = 10.

Q = zeros((2*d,2*d))
# First x
Q[0,0] = tauPsi + tauRho + tauPhi
Q[0,1] = -tauPsi
Q[0,d] = -tauPhi
Q[d,0] = -tauPhi
# Last x
Q[d-1,d-1] = tauPsi + tauRho + tauPhi
Q[d-1,d-2] = -tauPsi
Q[d-1,2*d-1] = -tauPhi
Q[2*d-1,d-1] = -tauPhi
for i in range(d)[1:d-1]:
    Q[i,i] = 2*tauPsi + tauRho + tauPhi
    Q[i,i-1] = -tauPsi
    Q[i,i+1] = -tauPsi
    Q[i,i+d] = -tauPhi
    Q[i+d,i] = -tauPhi

for i in range(d):
    Q[i+d,i+d] = tauPhi

P = inv(Q)

xExtended = random.multivariate_normal(zeros(2*d), P)
x[:,0] = xExtended[:d]
y[:,0] = xExtended[d:]

for t in arange(1,T):
    print t
    temp = r_[x[:,t-1],zeros(d)]
    mu = tauRho*a*dot(P,temp)
    xExtended = random.multivariate_normal(mu, P)
    x[:,t] = xExtended[:d]
    y[:,t] = xExtended[d:]
    
savetxt('simulatedData/d'+str(d)+'tauPhi'+str(tauPhi)+'y.txt', y)
savetxt('simulatedData/d'+str(d)+'tauPhi'+str(tauPhi)+'P.txt',P)


    

    




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In [11]:

    




    

In [13]:

    




    

In [98]:

    

imshow(abs(x-y))
colorbar()


    

    
Out[98]:





<matplotlib.colorbar.Colorbar instance at 0x7f4c4c1e1b90>






    

In [47]:

    




    

In [48]:

    




    

In [81]:

    




    

In [6]:

    

test1 = arange(3)
test2 = arange(5,9)


    

In [7]:

    

r_[test1,test2]


    

    
Out[7]:





array([0, 1, 2, 5, 6, 7, 8])

In [16]:

    

test = array([i+1.5 for i in range(10)])


    

In [14]:

    

test = zeros(5)


    

In [17]:

    

test


    

    
Out[17]:





array([  1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,  10.5])

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