Esempio n. 1
0
def main(G=5000000,iterations=50000,init_matrix=None,init_mu=None,verbose=True):
    """Test case for FD-inference"""
    print "generating genome"
    genome = random_site(G)
    print "generating eps"
    eps = score_genome_np(TRUE_ENERGY_MATRIX,genome)
    min_mu,max_mu = -40,0
    mu = bisect_interval(lambda mu:np.sum(fd_solve_np(eps,mu))-q,min_mu,max_mu,verbose=True,tolerance=1e-1)
    print "computing ps"
    true_ps = fd_solve_np(eps,mu)
    print "true q:",np.sum(true_ps)
    print "generating chip dataset"
    mapped_reads = np.array(map_reads_np(chip_ps_np(true_ps,MEAN_FRAGMENT_LENGTH,NUM_CELLS_ORIGINAL),G))
    print "finished chip dataset"
    if init_matrix is None:
        init_matrix = random_energy_matrix(w)
    if init_mu is None:
        init_mu = -20#random.random()*40 - 20
    init_scores = score_genome_np(init_matrix,genome)
    init_state = ((init_matrix,init_mu),init_scores)
    logf = lambda state:complete_log_likelihood(state,mapped_reads)
    print "true mu:",mu
    print "true log_likelihood:",logf(((TRUE_ENERGY_MATRIX,mu),eps))
    rprop = lambda state:complete_rprop(state,genome)
    print "hitting mh loop"
    matrix_chain = mh(logf,proposal=rprop,x0=init_state,dprop=log_dprop,capture_state=capture_state,verbose=verbose,use_log=True,iterations=iterations,modulus=100)
    return matrix_chain,genome,mapped_reads
Esempio n. 2
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def test_update_scores_np():
    w = 10
    matrix = random_energy_matrix(w)
    i = random.randrange(w)
    j = random.randrange(4)
    dw = random.random()
    print i,j,dw
    new_matrix = [row[:] for row in matrix]
    new_matrix[i][j] += dw
    genome = random_site(100000)
    fwd_scores,rev_scores = score_genome_np(matrix,genome,both_strands=True)
    fwd_scores_ref,rev_scores_ref = score_genome_np(new_matrix,genome,both_strands=True)
    fwd_scores_test,rev_scores_test = update_scores_np(fwd_scores,rev_scores,i,j,dw,w,genome)
    fwd_scores_ref2 = update_scores_np_ref(fwd_scores,i,j,dw,genome,w)
    print l2_np(fwd_scores_ref,fwd_scores_test),l2_np(fwd_scores_ref,fwd_scores_ref2)
    print l2_np(rev_scores_ref,rev_scores_test)