예제 #1
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    def test_nlineages(self):
        """
        Test lineage counting
        """
        k = 4
        n = 1e4
        rho = 1.5e-8 * 1
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)

        times = arghmm.get_time_points(ntimes=6)
        arghmm.discretize_arg(arg, times)
        tree = arg.get_marginal_tree(0)

        nlineages, nrecombs, ncoals = arghmm.get_nlineages_recomb_coal(
            tree, times)

        treelib.draw_tree_names(tree.get_tree(), scale=4e-3)

        print list(arghmm.iter_coal_states(tree, times))
        print nlineages
        self.assert_(nlineages == sorted(nlineages, reverse=True))

        print nlineages
        print nrecombs
        print ncoals
예제 #2
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    def test_prior(self):
        """
        Calculate state priors
        """

        k = 10
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points()
        arghmm.discretize_arg(arg, times)
        new_name = "n%d" % (k-1)
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        prior = [model.prob_prior(0, j)
                 for j in xrange(model.get_num_states(0))]
        print prior
        print sum(map(exp, prior))
        fequal(sum(map(exp, prior)), 1.0, rel=.01)
예제 #3
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def test_trans():
    """
    Calculate transition probabilities
    """
    create_data = False
    if create_data:
        make_clean_dir('test/data/test_trans')

    k = 8
    n = 1e4
    rho = 1.5e-8 * 20
    length = 1000
    times = argweaver.get_time_points(ntimes=10, maxtime=200000)
    popsizes = [n] * len(times)
    ntests = 40

    # generate test data
    if create_data:
        for i in range(ntests):
            arg = arglib.sample_arg(k, 2*n, rho, start=0, end=length)
            argweaver.discretize_arg(arg, times)
            arg.write('test/data/test_trans/%d.arg' % i)

    for i in range(ntests):
        print 'arg', i
        arg = arglib.read_arg('test/data/test_trans/%d.arg' % i)
        argweaver.discretize_arg(arg, times)
        pos = 10
        tree = arg.get_marginal_tree(pos)

        assert argweaverc.assert_transition_probs(tree, times, popsizes, rho)
예제 #4
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    def test_post(self):

        k = 6
        n = 1e4
        rho = 1.5e-8 * 10
        mu = 2.5e-8 * 10
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)
        print "muts", len(muts)
        print "recombs", len(arglib.get_recomb_pos(arg))

        times = arghmm.get_time_points(ntimes=10)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        # remove chrom
        new_name = "n%d" % (k - 1)
        keep = set(arg.leaf_names()) - set([new_name])
        arglib.subarg_by_leaf_names(arg, keep)
        arg = arglib.smcify_arg(arg)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name,
                              times=times, rho=rho, mu=mu)
        print "states", len(model.states[0])

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        for pcol in probs:
            p = sum(map(exp, pcol))
            print p, " ".join("%.3f" % f for f in map(exp, pcol))
            fequal(p, 1.0, rel=1e-2)
예제 #5
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    def test_trans_single(self):
        """
        Calculate transition probabilities

        Only calculate a single matrix
        """

        k = 4
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(10)
        arghmm.discretize_arg(arg, times)
        print "recomb", arglib.get_recomb_pos(arg)

        new_name = "n%d" % (k - 1)
        arg = arghmm.remove_arg_thread(arg, new_name)
        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        pos = 10
        tree = arg.get_marginal_tree(pos)
        mat = arghmm.calc_transition_probs(tree, model.states[pos],
                                           model.nlineages, model.times,
                                           model.time_steps, model.popsizes,
                                           rho)
        print model.states[pos]
        pc(mat)

        for row in mat:
            print sum(map(exp, row))
예제 #6
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    def test_trans_single(self):
        """
        Calculate transition probabilities

        Only calculate a single matrix
        """

        k = 4
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(10)
        arghmm.discretize_arg(arg, times)
        print "recomb", arglib.get_recomb_pos(arg)

        new_name = "n%d" % (k-1)
        arg = arghmm.remove_arg_thread(arg, new_name)
        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        pos = 10
        tree = arg.get_marginal_tree(pos)
        mat = arghmm.calc_transition_probs(
            tree, model.states[pos], model.nlineages,
            model.times, model.time_steps, model.popsizes, rho)
        print model.states[pos]
        pc(mat)

        for row in mat:
            print sum(map(exp, row))
예제 #7
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    def test_prior(self):
        """
        Calculate state priors
        """

        k = 10
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points()
        arghmm.discretize_arg(arg, times)
        new_name = "n%d" % (k - 1)
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        prior = [
            model.prob_prior(0, j) for j in xrange(model.get_num_states(0))
        ]
        print prior
        print sum(map(exp, prior))
        fequal(sum(map(exp, prior)), 1.0, rel=.01)
예제 #8
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    def test_nlineages(self):
        """
        Test lineage counting
        """
        k = 4
        n = 1e4
        rho = 1.5e-8 * 1
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)

        times = arghmm.get_time_points(ntimes=6)
        arghmm.discretize_arg(arg, times)
        tree = arg.get_marginal_tree(0)

        nlineages, nrecombs, ncoals = arghmm.get_nlineages_recomb_coal(
            tree, times)

        treelib.draw_tree_names(tree.get_tree(), scale=4e-3)

        print list(arghmm.iter_coal_states(tree, times))
        print nlineages
        self.assert_(nlineages == sorted(nlineages, reverse=True))

        print nlineages
        print nrecombs
        print ncoals
예제 #9
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    def test_post_plot(self):

        k = 6
        n = 1e4
        rho = 1.5e-8 * 50
        mu = 2.5e-8 * 50
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(ntimes=30)
        arghmm.discretize_arg(arg, times)

        pause()

        # save
        #arglib.write_arg("test/data/k4.arg", arg)
        #fasta.write_fasta("test/data/k4.fa", seqs)

        new_name = "n%d" % (k - 1)
        thread = list(
            arghmm.iter_chrom_thread(arg, arg[new_name], by_block=False))
        p = plot(cget(thread, 1), style="lines", ymin=times[1], ylog=10)

        # remove chrom
        new_name = "n%d" % (k - 1)
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name=new_name,
                              times=times,
                              rho=rho,
                              mu=mu)
        print "states", len(model.states[0])
        print "muts", len(muts)
        print "recomb", len(model.recomb_pos) - 2, model.recomb_pos[1:-1]

        p.plot(model.recomb_pos, [10000] * len(model.recomb_pos),
               style="points")

        probs = arghmm.get_posterior_probs(model, length, verbose=True)
        print "done"

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.gnuplot("set linestyle 2")
        p.plot(high, style="lines")
        p.gnuplot("set linestyle 2")
        p.plot(low, style="lines")

        #write_list("test/data/post_real.txt", cget(thread, 1))
        #write_list("test/data/post_high.txt", high)
        #write_list("test/data/post_low.txt", low)

        pause()
예제 #10
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    def test_post_plot(self):

        k = 6
        n = 1e4
        rho = 1.5e-8 * 50
        mu = 2.5e-8 * 50
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(ntimes=30)
        arghmm.discretize_arg(arg, times)

        pause()

        # save
        #arglib.write_arg("test/data/k4.arg", arg)
        #fasta.write_fasta("test/data/k4.fa", seqs)

        new_name = "n%d" % (k-1)
        thread = list(arghmm.iter_chrom_thread(arg, arg[new_name],
                                               by_block=False))
        p = plot(cget(thread, 1), style="lines", ymin=times[1],
                 ylog=10)

        # remove chrom
        new_name = "n%d" % (k-1)
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times,
                              rho=rho, mu=mu)
        print "states", len(model.states[0])
        print "muts", len(muts)
        print "recomb", len(model.recomb_pos) - 2, model.recomb_pos[1:-1]

        p.plot(model.recomb_pos, [10000] * len(model.recomb_pos),
               style="points")

        probs = arghmm.get_posterior_probs(model, length, verbose=True)
        print "done"

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.gnuplot("set linestyle 2")
        p.plot(high, style="lines")
        p.gnuplot("set linestyle 2")
        p.plot(low, style="lines")


        #write_list("test/data/post_real.txt", cget(thread, 1))
        #write_list("test/data/post_high.txt", high)
        #write_list("test/data/post_low.txt", low)

        pause()
예제 #11
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    def test_norecomb_plot(self):

        k = 50
        n = 1e4
        rho = 1.5e-8 * .0001
        rho2 = 1.5e-8 * 10
        mu = 2.5e-8 * 100
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(ntimes=20)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        # get thread
        new_name = "n%d" % (k - 1)
        keep = ["n%d" % i for i in range(k - 1)]
        arglib.subarg_by_leaf_names(arg, keep)
        arg.set_ancestral()
        arg.prune()

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name=new_name,
                              times=times,
                              rho=rho2,
                              mu=mu)
        print "states", len(model.states[0])
        print "muts", len(muts)

        # simulate a new thread
        states = list(islice(hmm.sample_hmm_states(model), 0, arg.end))
        data = list(hmm.sample_hmm_data(model, states))

        seqs[new_name] = "".join(data)
        #alignlib.print_align(seqs)

        thread = [
            model.times[model.states[i][s][1]] for i, s in enumerate(states)
        ]
        p = plot(thread, style="lines")

        probs = arghmm.get_posterior_probs(model, length, verbose=True)
        print "done"

        high = list(arghmm.iter_posterior_times(model, probs, .75))
        low = list(arghmm.iter_posterior_times(model, probs, .25))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #12
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    def test_local_trees(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 10000      # length of locus
        k = 10         # number of lineages
        n = 2*1e4      # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)
        blocks1 = util.cget(arglib.iter_local_trees(arg, 200, 1200), 0)
        blocks2 = list(arglib.iter_recomb_blocks(arg, 200, 1200))
        self.assertEqual(blocks1, blocks2)
예제 #13
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    def test_post_real(self):

        k = 3
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8
        length = 100000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        #arg = arglib.read_arg("test/data/real.arg")
        #seqs = fasta.read_fasta("test/data/real.fa")

        #arglib.write_arg("test/data/real.arg", arg)
        #fasta.write_fasta("test/data/real.fa", seqs)

        times = arghmm.get_time_points(maxtime=50000, ntimes=20)
        arghmm.discretize_arg(arg, times)

        new_name = "n%d" % (k - 1)
        thread = list(
            arghmm.iter_chrom_thread(arg, arg[new_name], by_block=False))
        tree = arg.get_marginal_tree(0)
        print tree.root.age
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)
        p = plot(cget(thread, 1), style="lines", ymin=10, ylog=10)

        #alignlib.print_align(seqs)

        # remove chrom
        keep = ["n%d" % i for i in range(k - 1)]
        arglib.subarg_by_leaf_names(arg, keep)
        arg = arglib.smcify_arg(arg)

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name=new_name,
                              times=times,
                              rho=rho,
                              mu=mu)

        print "states", len(model.states[0])
        #print "muts", len(muts)
        print "recomb", len(model.recomb_pos) - 2, model.recomb_pos[1:-1]

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #14
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    def test_iter_sprs(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 100000     # length of locus
        k = 6          # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)

        for a, b in izip(arglib.iter_arg_sprs(arg),
                         arglib.iter_arg_sprs_simple(arg)):
            self.assertEqual(a, b)
예제 #15
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    def test_smcify_arg(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 100000     # length of locus
        k = 6          # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)
        arg = arglib.smcify_arg(arg)

        for pos, (rnode, rtime), (cnode, ctime) in arglib.iter_arg_sprs(arg):
            self.assertNotEqual(rnode, cnode)
예제 #16
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    def test_trans_switch_single(self):
        """
        Calculate transitions probabilities for switching between blocks

        Only calculate a single matrix
        """

        k = 5
        n = 1e4
        rho = 1.5e-8 * 100
        mu = 2.5e-8
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        #arglib.write_arg("tmp/a.arg", arg)
        #arg = arglib.read_arg("tmp/a.arg")
        #arg.set_ancestral()

        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(5)
        arghmm.discretize_arg(arg, times)

        new_name = "n%d" % (k - 1)
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        # get recombs
        recombs = list(x.pos for x in arghmm.iter_visible_recombs(arg))
        print "recomb", recombs

        pos = recombs[0] + 1
        tree = arg.get_marginal_tree(pos - .5)
        last_tree = arg.get_marginal_tree(pos - 1 - .5)

        print "states1>>", model.states[pos - 1]
        print "states2>>", model.states[pos]

        treelib.draw_tree_names(last_tree.get_tree(), minlen=5, maxlen=5)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, maxlen=5)

        print "pos>>", pos
        recomb = [x for x in tree
                  if x.event == "recomb" and x.pos + 1 == pos][0]
        mat = arghmm.calc_transition_probs_switch(tree, last_tree, recomb.name,
                                                  model.states[pos - 1],
                                                  model.states[pos],
                                                  model.nlineages, model.times,
                                                  model.time_steps,
                                                  model.popsizes, rho)
        pc(mat)
예제 #17
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    def test_norecomb_plot(self):

        k = 50
        n = 1e4
        rho = 1.5e-8 * .0001
        rho2 = 1.5e-8 * 10
        mu = 2.5e-8 * 100
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)


        times = arghmm.get_time_points(ntimes=20)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        # get thread
        new_name = "n%d" % (k-1)
        keep = ["n%d" % i for i in range(k-1)]
        arglib.subarg_by_leaf_names(arg, keep)
        arg.set_ancestral()
        arg.prune()

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times,
                              rho=rho2, mu=mu)
        print "states", len(model.states[0])
        print "muts", len(muts)

        # simulate a new thread
        states = list(islice(hmm.sample_hmm_states(model), 0, arg.end))
        data = list(hmm.sample_hmm_data(model, states))

        seqs[new_name] = "".join(data)
        #alignlib.print_align(seqs)

        thread = [model.times[model.states[i][s][1]]
                  for i, s in enumerate(states)]
        p = plot(thread, style="lines")


        probs = arghmm.get_posterior_probs(model, length, verbose=True)
        print "done"

        high = list(arghmm.iter_posterior_times(model, probs, .75))
        low = list(arghmm.iter_posterior_times(model, probs, .25))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #18
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    def test_trans_switch_single(self):
        """
        Calculate transitions probabilities for switching between blocks

        Only calculate a single matrix
        """

        k = 5
        n = 1e4
        rho = 1.5e-8 * 100
        mu = 2.5e-8
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        #arglib.write_arg("tmp/a.arg", arg)
        #arg = arglib.read_arg("tmp/a.arg")
        #arg.set_ancestral()


        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(5)
        arghmm.discretize_arg(arg, times)

        new_name = "n%d" % (k-1)
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        # get recombs
        recombs = list(x.pos for x in arghmm.iter_visible_recombs(arg))
        print "recomb", recombs

        pos = recombs[0] + 1
        tree = arg.get_marginal_tree(pos-.5)
        last_tree = arg.get_marginal_tree(pos-1-.5)

        print "states1>>", model.states[pos-1]
        print "states2>>", model.states[pos]

        treelib.draw_tree_names(last_tree.get_tree(), minlen=5, maxlen=5)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, maxlen=5)

        print "pos>>", pos
        recomb = [x for x in tree
                  if x.event == "recomb" and x.pos+1 == pos][0]
        mat = arghmm.calc_transition_probs_switch(
            tree, last_tree, recomb.name,
            model.states[pos-1], model.states[pos],
            model.nlineages, model.times,
            model.time_steps, model.popsizes, rho)
        pc(mat)
예제 #19
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    def test_post_c(self):

        k = 3
        n = 1e4
        rho = 1.5e-8 * 30
        mu = 2.5e-8 * 100
        length = 100
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        arg.prune()
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        print arglib.get_recomb_pos(arg)
        print "muts", len(muts)
        print "recomb", len(arglib.get_recomb_pos(arg))

        times = arghmm.get_time_points(ntimes=10)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        print tree.root.age
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        # remove chrom
        keep = ["n%d" % i for i in range(k - 1)]
        arglib.subarg_by_leaf_names(arg, keep)

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name="n%d" % (k - 1),
                              times=times,
                              rho=rho,
                              mu=mu)
        print "states", len(model.states[0])

        util.tic("C")
        probs1 = list(arghmm.get_posterior_probs(model, length, verbose=True))
        util.toc()

        util.tic("python")
        probs2 = list(hmm.get_posterior_probs(model, length, verbose=True))
        util.toc()

        print "probs1"
        pc(probs1)

        print "probs2"
        pc(probs2)

        for col1, col2 in izip(probs1, probs2):
            for a, b in izip(col1, col2):
                fequal(a, b)
예제 #20
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    def test_smcify_arg_remove_thread(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 100000      # length of locus
        k = 6         # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)
        remove_chroms = set("n%d" % (k-1))
        keep = [x for x in arg.leaf_names() if x not in remove_chroms]
        arg = arg.copy()
        arglib.subarg_by_leaf_names(arg, keep)
        arg = arglib.smcify_arg(arg)
예제 #21
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    def test_post_real(self):

        k = 3
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8
        length = 100000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        #arg = arglib.read_arg("test/data/real.arg")
        #seqs = fasta.read_fasta("test/data/real.fa")

        #arglib.write_arg("test/data/real.arg", arg)
        #fasta.write_fasta("test/data/real.fa", seqs)

        times = arghmm.get_time_points(maxtime=50000, ntimes=20)
        arghmm.discretize_arg(arg, times)

        new_name = "n%d" % (k - 1)
        thread = list(arghmm.iter_chrom_thread(arg, arg[new_name],
                                               by_block=False))
        tree = arg.get_marginal_tree(0)
        print tree.root.age
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)
        p = plot(cget(thread, 1), style="lines", ymin=10, ylog=10)

        #alignlib.print_align(seqs)

        # remove chrom
        keep = ["n%d" % i for i in range(k-1)]
        arglib.subarg_by_leaf_names(arg, keep)
        arg = arglib.smcify_arg(arg)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times,
                              rho=rho, mu=mu)

        print "states", len(model.states[0])
        #print "muts", len(muts)
        print "recomb", len(model.recomb_pos) - 2, model.recomb_pos[1:-1]

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #22
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    def test_iter_sprs_time(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 100000     # length of locus
        k = 40         # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)

        x = list(arglib.iter_arg_sprs(arg))
        x = list(arglib.iter_arg_sprs_simple(arg))
        x = list(arglib.iter_arg_sprs(arg, use_leaves=True))
        x = list(arglib.iter_arg_sprs_simple(arg, use_leaves=True))
        x
예제 #23
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    def test_post_c(self):

        k = 3
        n = 1e4
        rho = 1.5e-8 * 30
        mu = 2.5e-8 * 100
        length = 100
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        arg.prune()
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        print arglib.get_recomb_pos(arg)
        print "muts", len(muts)
        print "recomb", len(arglib.get_recomb_pos(arg))

        times = arghmm.get_time_points(ntimes=10)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        print tree.root.age
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        # remove chrom
        keep = ["n%d" % i for i in range(k-1)]
        arglib.subarg_by_leaf_names(arg, keep)

        model = arghmm.ArgHmm(arg, seqs, new_name="n%d" % (k-1), times=times,
                              rho=rho, mu=mu)
        print "states", len(model.states[0])

        util.tic("C")
        probs1 = list(arghmm.get_posterior_probs(model, length, verbose=True))
        util.toc()

        util.tic("python")
        probs2 = list(hmm.get_posterior_probs(model, length, verbose=True))
        util.toc()

        print "probs1"
        pc(probs1)

        print "probs2"
        pc(probs2)


        for col1, col2 in izip(probs1, probs2):
            for a, b in izip(col1, col2):
                fequal(a, b)
예제 #24
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    def test_post3(self):

        k = 3
        n = 1e4
        rho = 1.5e-8 * 3
        mu = 2.5e-8 * 100
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        arg.prune()
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(ntimes=10)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        thread = list(arghmm.iter_chrom_thread(arg, arg["n2"], by_block=False))
        p = plot(cget(thread, 1), style="lines", ymin=0)

        # remove chrom
        keep = ["n0", "n1"]
        arglib.subarg_by_leaf_names(arg, keep)
        arg.set_ancestral()
        arg.prune()

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name="n2",
                              times=times,
                              rho=rho,
                              mu=mu)
        print "states", len(model.states[0])
        print "muts", len(muts)
        print "recomb", len(model.recomb_pos) - 2, model.recomb_pos[1:-1]

        p.plot(model.recomb_pos, [1000] * len(model.recomb_pos),
               style="points")

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #25
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    def test_iter_sprs_remove_thread(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 100000     # length of locus
        k = 6          # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)
        remove_chroms = set("n%d" % (k-1))
        keep = [x for x in arg.leaf_names() if x not in remove_chroms]
        arg = arg.copy()
        arglib.subarg_by_leaf_names(arg, keep)

        for a, b in izip(arglib.iter_arg_sprs(arg),
                         arglib.iter_arg_sprs_simple(arg)):
            self.assertEqual(a, b)
예제 #26
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    def test_iter_sprs_leaves(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 100000     # length of locus
        k = 40         # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)

        for a, b in izip(arglib.iter_arg_sprs(arg, use_leaves=True),
                         arglib.iter_arg_sprs_simple(arg, use_leaves=True)):
            a[1][0].sort()
            a[2][0].sort()
            b[1][0].sort()
            b[2][0].sort()
            self.assertEqual(a, b)
예제 #27
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    def test_marginal_leaves(self):

        rho = 1.5e-8   # recomb/site/gen
        l = 10000      # length of locus
        k = 10         # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)

        for (start, end), tree in arglib.iter_local_trees(arg):
            arglib.remove_single_lineages(tree)
            mid = (start + end) / 2.0
            for node in tree:
                a = set(tree.leaves(node))
                b = set(arglib.get_marginal_leaves(arg, node, mid))
                self.assertEqual(a, b)
예제 #28
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    def test_post3(self):

        k = 3
        n = 1e4
        rho = 1.5e-8 * 3
        mu = 2.5e-8 * 100
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        arg.prune()
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(ntimes=10)
        arghmm.discretize_arg(arg, times)


        tree = arg.get_marginal_tree(0)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        thread = list(arghmm.iter_chrom_thread(arg, arg["n2"], by_block=False))
        p = plot(cget(thread, 1), style="lines", ymin=0)

        # remove chrom
        keep = ["n0", "n1"]
        arglib.subarg_by_leaf_names(arg, keep)
        arg.set_ancestral()
        arg.prune()


        model = arghmm.ArgHmm(arg, seqs, new_name="n2", times=times,
                              rho=rho, mu=mu)
        print "states", len(model.states[0])
        print "muts", len(muts)
        print "recomb", len(model.recomb_pos) - 2, model.recomb_pos[1:-1]


        p.plot(model.recomb_pos, [1000] * len(model.recomb_pos),
               style="points")

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #29
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    def test_post2(self):

        k = 2
        n = 1e4
        rho = 1.5e-8 * 10
        mu = 2.5e-8 * 10
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        print "muts", len(muts)

        times = arghmm.get_time_points()
        arghmm.discretize_arg(arg, times)

        thread = list(arghmm.iter_chrom_thread(arg, arg["n1"], by_block=False))
        tree = arg.get_marginal_tree(0)
        print tree.root.age
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)
        p = plot(cget(thread, 1), style="lines", ymin=0)

        #alignlib.print_align(seqs)

        # remove chrom
        keep = ["n0"]
        arglib.subarg_by_leaf_names(arg, keep)
        arg = arglib.smcify_arg(arg)

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name="n1",
                              times=times,
                              rho=rho,
                              mu=mu)
        print "states", len(model.states[0])

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #30
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    def test_plot_thread(self):
        """
        Test thread retrieval
        """

        k = 60
        n = 1e4
        rho = 1.5e-8 * 20
        mu = 2.5e-8 * 20
        length = int(1000e3) / 20
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)

        node = arg.leaves().next()
        x = range(length)
        y = cget(arghmm.iter_chrom_thread(arg, node, by_block=False), 1)

        p = plot(x, y, style='lines')

        pause()
예제 #31
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    def test_plot_thread(self):
        """
        Test thread retrieval
        """

        k = 60
        n = 1e4
        rho = 1.5e-8 * 20
        mu = 2.5e-8 * 20
        length = int(1000e3) / 20
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)

        node = arg.leaves().next()
        x = range(length)
        y = cget(arghmm.iter_chrom_thread(arg, node, by_block=False), 1)

        p = plot(x, y, style='lines')

        pause()
예제 #32
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def test_trans():
    """
    Calculate transition probabilities
    """

    k = 4
    n = 1e4
    rho = 1.5e-8 * 20
    length = 1000
    times = argweaver.get_time_points(ntimes=4, maxtime=200000)
    popsizes = [n] * len(times)

    arg = arglib.sample_arg(k, 2*n, rho, start=0, end=length)
    argweaver.discretize_arg(arg, times)

    pos = 10
    tree = arg.get_marginal_tree(pos)

    assert argweaverc.assert_transition_probs(tree, times, popsizes, rho)
예제 #33
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def test_trans():
    """
    Calculate transition probabilities
    """

    k = 4
    n = 1e4
    rho = 1.5e-8 * 20
    length = 1000
    times = argweaver.get_time_points(ntimes=4, maxtime=200000)
    popsizes = [n] * len(times)

    arg = arglib.sample_arg(k, 2 * n, rho, start=0, end=length)
    argweaver.discretize_arg(arg, times)

    pos = 10
    tree = arg.get_marginal_tree(pos)

    assert argweaverc.assert_transition_probs(tree, times, popsizes, rho)
예제 #34
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    def test_read_write(self):
        """Read and write an ARG"""

        rho = 1.5e-8   # recomb/site/gen
        l = 10000      # length of locus
        k = 10         # number of lineages
        n = 2*10000    # effective popsize

        arg = arglib.sample_arg(k, n, rho, 0, l)
        # round ages and pos for easy equality
        for node in arg:
            node.age = round(node.age)
            node.pos = round(node.pos)

        stream = StringIO.StringIO()
        arglib.write_arg(stream, arg)
        stream.seek(0)
        arg2 = arglib.read_arg(stream)

        self.assertTrue(arg.equal(arg2))
예제 #35
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    def test_thread(self):
        """
        Test thread retrieval
        """

        k = 10
        n = 1e4
        rho = 1.5e-8 * 10
        mu = 2.5e-8 * 100
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        for (block, tree), threadi in izip(
            arglib.iter_tree_tracks(arg),
            arghmm.iter_chrom_thread(arg, arg["n9"], by_block=True)):
            print block
            print threadi
            treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)
예제 #36
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    def test_thread(self):
        """
        Test thread retrieval
        """

        k = 10
        n = 1e4
        rho = 1.5e-8 * 10
        mu = 2.5e-8 * 100
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        for (block, tree), threadi in izip(
                arglib.iter_tree_tracks(arg),
                arghmm.iter_chrom_thread(arg, arg["n9"], by_block=True)):
            print block
            print threadi
            treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)
예제 #37
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    def test_post2(self):

        k = 2
        n = 1e4
        rho = 1.5e-8 * 10
        mu = 2.5e-8 * 10
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        print "muts", len(muts)

        times = arghmm.get_time_points()
        arghmm.discretize_arg(arg, times)

        thread = list(arghmm.iter_chrom_thread(arg, arg["n1"], by_block=False))
        tree = arg.get_marginal_tree(0)
        print tree.root.age
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)
        p = plot(cget(thread, 1), style="lines", ymin=0)

        #alignlib.print_align(seqs)

        # remove chrom
        keep = ["n0"]
        arglib.subarg_by_leaf_names(arg, keep)
        arg = arglib.smcify_arg(arg)

        model = arghmm.ArgHmm(arg, seqs, new_name="n1", times=times,
                              rho=rho, mu=mu)
        print "states", len(model.states[0])

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        high = list(arghmm.iter_posterior_times(model, probs, .95))
        low = list(arghmm.iter_posterior_times(model, probs, .05))
        p.plot(high, style="lines")
        p.plot(low, style="lines")

        pause()
예제 #38
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    def test_states(self):
        """
        Test state enumeration
        """
        k = 2
        n = 1e4
        rho = 1.5e-8 * 100
        length = 1000

        for i in xrange(20):
            arg = arglib.sample_arg(k, n, rho, start=0, end=length)

            times = arghmm.get_time_points(10)
            arghmm.discretize_arg(arg, times)
            tree = arg.get_marginal_tree(0)

            states = list(arghmm.iter_coal_states(tree, times))

            treelib.draw_tree_names(tree.get_tree(), scale=4e-4,
                                    minlen=6, maxlen=6)
            print states
예제 #39
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    def test_emit_argmax(self):
        """
        Calculate emission probabilities
        """

        k = 10
        n = 1e4
        rho = 0.0
        mu = 2.5e-8 * 100
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(10)
        arghmm.discretize_arg(arg, times)

        new_name = "n%d" % (k-1)
        thread = list(arghmm.iter_chrom_thread(arg, arg[new_name]))
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        nstates = model.get_num_states(1)
        probs = [0.0 for j in xrange(nstates)]
        for i in xrange(1, length):
            if i % 100 == 0:
                print i
            for j in xrange(nstates):
                probs[j] += model.prob_emission(i, j)
        print

        # is the maximum likelihood emission matching truth
        data = sorted(zip(probs, model.states[0]), reverse=True)
        pc(data[:20])

        state = (thread[0][0], times.index(thread[0][1]))

        print data[0][1], state
        assert data[0][1] == state
예제 #40
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    def test_emit_argmax(self):
        """
        Calculate emission probabilities
        """

        k = 10
        n = 1e4
        rho = 0.0
        mu = 2.5e-8 * 100
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(10)
        arghmm.discretize_arg(arg, times)

        new_name = "n%d" % (k - 1)
        thread = list(arghmm.iter_chrom_thread(arg, arg[new_name]))
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)

        nstates = model.get_num_states(1)
        probs = [0.0 for j in xrange(nstates)]
        for i in xrange(1, length):
            if i % 100 == 0:
                print i
            for j in xrange(nstates):
                probs[j] += model.prob_emission(i, j)
        print

        # is the maximum likelihood emission matching truth
        data = sorted(zip(probs, model.states[0]), reverse=True)
        pc(data[:20])

        state = (thread[0][0], times.index(thread[0][1]))

        print data[0][1], state
        assert data[0][1] == state
예제 #41
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    def test_backward(self):
        """
        Run backward algorithm
        """

        k = 3
        n = 1e4
        rho = 1.5e-8 * 100
        mu = 2.5e-8 * 100
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        times = arghmm.get_time_points(ntimes=10)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        print tree.root.age
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        # remove chrom
        new_name = "n%d" % (k - 1)
        arg = arghmm.remove_arg_thread(arg, new_name)

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name=new_name,
                              times=times,
                              rho=rho,
                              mu=mu)
        print "states", len(model.states[0])
        print "recomb", model.recomb_pos
        print "muts", len(muts)

        probs = hmm.backward_algorithm(model, length, verbose=True)

        for pcol in probs:
            p = sum(map(exp, pcol))
            print p, " ".join("%.3f" % f for f in map(exp, pcol))
예제 #42
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    def test_trans(self):
        """
        Calculate transition probabilities for k=2

        Only calculate a single matrix
        """

        k = 4
        n = 1e4
        rho = 1.5e-8 * 20
        mu = 2.5e-8 * 20
        length = 1000
        times = arghmm.get_time_points(ntimes=4, maxtime=200000)
        popsizes = [n] * len(times)

        arg = arglib.sample_arg(k, 2*n, rho, start=0, end=length)
        arghmm.discretize_arg(arg, times)

        pos = 10
        tree = arg.get_marginal_tree(pos)

        assert arghmm.assert_transition_probs(tree, times, popsizes, rho)
예제 #43
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def test_trans_internal():
    """
    Calculate transition probabilities for internal branch re-sampling

    Only calculate a single matrix
    """

    k = 5
    n = 1e4
    rho = 1.5e-8 * 20
    length = 1000
    times = argweaver.get_time_points(ntimes=5, maxtime=200000)
    popsizes = [n] * len(times)

    arg = arglib.sample_arg(k, 2 * n, rho, start=0, end=length)
    argweaver.discretize_arg(arg, times)

    pos = 10
    tree = arg.get_marginal_tree(pos)

    assert argweaverc.assert_transition_probs_internal(tree, times, popsizes,
                                                       rho)
예제 #44
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def test_trans_internal():
    """
    Calculate transition probabilities for internal branch re-sampling

    Only calculate a single matrix
    """

    k = 5
    n = 1e4
    rho = 1.5e-8 * 20
    length = 1000
    times = argweaver.get_time_points(ntimes=5, maxtime=200000)
    popsizes = [n] * len(times)

    arg = arglib.sample_arg(k, 2*n, rho, start=0, end=length)
    argweaver.discretize_arg(arg, times)

    pos = 10
    tree = arg.get_marginal_tree(pos)

    assert argweaverc.assert_transition_probs_internal(
        tree, times, popsizes, rho)
예제 #45
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    def test_post(self):

        k = 6
        n = 1e4
        rho = 1.5e-8 * 10
        mu = 2.5e-8 * 10
        length = 10000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)
        print "muts", len(muts)
        print "recombs", len(arglib.get_recomb_pos(arg))

        times = arghmm.get_time_points(ntimes=10)
        arghmm.discretize_arg(arg, times)

        tree = arg.get_marginal_tree(0)
        treelib.draw_tree_names(tree.get_tree(), minlen=5, scale=4e-4)

        # remove chrom
        new_name = "n%d" % (k - 1)
        keep = set(arg.leaf_names()) - set([new_name])
        arglib.subarg_by_leaf_names(arg, keep)
        arg = arglib.smcify_arg(arg)

        model = arghmm.ArgHmm(arg,
                              seqs,
                              new_name=new_name,
                              times=times,
                              rho=rho,
                              mu=mu)
        print "states", len(model.states[0])

        probs = arghmm.get_posterior_probs(model, length, verbose=True)

        for pcol in probs:
            p = sum(map(exp, pcol))
            print p, " ".join("%.3f" % f for f in map(exp, pcol))
            fequal(p, 1.0, rel=1e-2)
예제 #46
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    def test_trans(self):
        """
        Calculate transition probabilities for k=2

        Only calculate a single matrix
        """

        k = 4
        n = 1e4
        rho = 1.5e-8 * 20
        mu = 2.5e-8 * 20
        length = 1000
        times = arghmm.get_time_points(ntimes=4, maxtime=200000)
        popsizes = [n] * len(times)

        arg = arglib.sample_arg(k, 2 * n, rho, start=0, end=length)
        arghmm.discretize_arg(arg, times)

        pos = 10
        tree = arg.get_marginal_tree(pos)

        assert arghmm.assert_transition_probs(tree, times, popsizes, rho)
예제 #47
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    def test_pars_seq(self):
        """
        Test parsimony ancestral sequence inference
        """

        k = 10
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8 * 100
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        pos = int(muts[0][2])
        tree = arg.get_marginal_tree(pos)

        print "pos =", pos
        treelib.draw_tree_names(tree.get_tree(), scale=4e-4, minlen=5)

        arglib.remove_single_lineages(tree)
        ancestral = arghmm.emit.parsimony_ancestral_seq(tree, seqs, pos)
        util.print_dict(ancestral)
예제 #48
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    def test_pars_seq(self):
        """
        Test parsimony ancestral sequence inference
        """

        k = 10
        n = 1e4
        rho = 1.5e-8
        mu = 2.5e-8 * 100
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)
        muts = arglib.sample_arg_mutations(arg, mu)
        seqs = arglib.make_alignment(arg, muts)

        pos = int(muts[0][2])
        tree = arg.get_marginal_tree(pos)

        print "pos =", pos
        treelib.draw_tree_names(tree.get_tree(), scale=4e-4, minlen=5)

        arglib.remove_single_lineages(tree)
        ancestral = arghmm.emit.parsimony_ancestral_seq(tree, seqs, pos)
        util.print_dict(ancestral)
예제 #49
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    def test_states(self):
        """
        Test state enumeration
        """
        k = 2
        n = 1e4
        rho = 1.5e-8 * 100
        length = 1000

        for i in xrange(20):
            arg = arglib.sample_arg(k, n, rho, start=0, end=length)

            times = arghmm.get_time_points(10)
            arghmm.discretize_arg(arg, times)
            tree = arg.get_marginal_tree(0)

            states = list(arghmm.iter_coal_states(tree, times))

            treelib.draw_tree_names(tree.get_tree(),
                                    scale=4e-4,
                                    minlen=6,
                                    maxlen=6)
            print states
예제 #50
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    def test_recomb(self):
        """
        Investigate the fact that some recombinations are not visible
        """

        k = 3
        n = 1e4
        rho = 1.5e-8 * 20
        mu = 2.5e-8
        length = 1000
        arg = arglib.sample_arg(k, n, rho, start=0, end=length)

        times = arghmm.get_time_points(10)
        arghmm.discretize_arg(arg, times)
        arg.set_ancestral()
        arg.prune()

        recombs = arglib.get_recomb_pos(arg)

        # find recombs by walking
        recombs2 = []
        i = 0
        while True:
            tree = arg.get_marginal_tree(i-.5)
            recomb = arghmm.find_tree_next_recomb(tree, i+1, tree=True)
            if recomb:
                recombs2.append(recomb.pos)
                i = recomb.pos
            else:
                break

        # these are suppose to differ because some recombination occur
        # in the hole of ancestral sequence intervals
        print recombs
        print recombs2

        arglib.write_arg("tmp/b.arg", arg)