def random_walks_by_chunk_get_score_sparse_matrix(mym1,mym2,tmin,tmax,nonzero_total,chunksize):
scores=[]
n=mym1.shape[0]
m1_t=mym1.transpose()
m2_t=mym2.transpose()
mat_names[1]='mats'
for t in range(1,(tmax+1)):
if t!=1:
compute_current_matrices(t,mat_names)
if t>=tmin:
pass
#scores.append(1.0*abs_diff_by_chunk_sparse_matrix(t)/nonzero_total)
print 'done '+str(t)+' '+strftime("%c")
return scores
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