2 into 1 Python help!!!

[kostasko]

Hi everyone,

First of all I would like to say that I do not know anything about Python. However, I got this program today and I think I understand more or less what it does. From the results it gives me I think that it does a similar thing twice. So at the end it provides me with two datasets. I would like to shorten the code to do just one thing at a time. For example where at the beginning it says

S=(2,3)
mocapy_seed(S[0], S[1]). Although I do not understand what it means It gives at the output two datasets.

I cannot do it myself because it gives me errrors that I do not understand at all. As I said I do not know Python. Here is the code:

from numpy import *
from numpy.random import random, seed
import sys

from Mocapy import *


# seed
S=(2,3)
mocapy_seed(S[0], S[1])

# nr of sequences
N=15
# seq lengths
T=15

MCMC_STEPS=1
MCMC_BURN_IN=1

H_SIZE=2
DIM=3

TUM=array(((1,0,0), (1,0,0)), 'd')
TUK=array([15]*H_SIZE, 'd')

MUM=array(((10, 9.3), (5.3, 7.1)), 'd')
MUM=None
MUK=array([10]*H_SIZE, 'd')

# The target DBN
th0=DiscreteNode(node_size=H_SIZE)
th1=DiscreteNode(node_size=H_SIZE)
to0=VMFNode(dim=DIM, node_size=H_SIZE, user_mus=TUM, user_kappas=TUK)

start_nodes=[th0, to0]
end_nodes=[th1, to0]
node_list=[th0, th1, to0]

tdbn=DBN(start_nodes, end_nodes)

tdbn.add_intra(0, 1)
tdbn.add_inter(0, 0)

tdbn.construct()

# The model DBN
mh0=DiscreteNode(node_size=H_SIZE, user_cpd=th0.cpd)
mh0.fixed=1
mh1=DiscreteNode(node_size=H_SIZE)
mo0=VMFNode(dim=DIM, node_size=H_SIZE, user_mus=MUM, user_kappas=MUK)

start_nodes=[mh0, mo0]
end_nodes=[mh1, mo0]
node_list=[mh0, mh1, mo0]

mdbn=DBN(start_nodes, end_nodes)

mdbn.add_intra(0, 1)
mdbn.add_inter(0, 0)

mdbn.construct()

# Generate the data
seq_list=[]
mismask_list=[]

if mpi.rank==0:
# Write the data to a file
fp=open("hmm_vmf.data", "w")
for i in range(0, N):
seq, ll=tdbn.sample_sequence(T)
for l in range(0, T):
fp.write(("%f "*DIM+"\n") % tuple(seq[l,1:]))
seq_list.append(seq)
mismask=zeros((T,2))
mismask[:,0]=1
mismask_list.append(mismask)
fp.close()
else:
seq_list=[]
mismask_list=[]

local_seq_list=mpi.scatter(seq_list)
local_mismask_list=mpi.scatter(mismask_list)

mcmc=GibbsRandom(mdbn)

em=EMEngine(mdbn, mcmc, local_seq_list, local_mismask_list)

iteration=1

print th0
print th1
print to0

print "-"*40

print mh0
print mh1
print mo0

while 1:
print "-"*40

if mpi.rank==0:
print "Iteration ", iteration
print "Running on %i nodes." % mpi.size
sys.stdout.flush()

if iteration==1:
em.do_E_step(MCMC_STEPS, MCMC_BURN_IN)
else:
em.do_E_step(MCMC_STEPS, 0, 0)

ll=em.get_loglik()

if mpi.rank==0:
print "LL ", ll
sys.stdout.flush()

print mh0
print mh1
print mo0

em.do_M_step()

sys.stdout.flush()

iteration+=1

Your help will be very much appreciated

Thanks

Regards

Kostas

 

[eclecticNancy]

Even closer to the beginning...

from numpy import *
from numpy.random import random, seed
from Mocapy import *

Do you actually have the numpy and Mocapy modules? I'm not familiar with them.

Also, the errors would help people answer your questions, even if you do not understand what they say.

-Nancy