Python sort_phylogenetically Examples

Example #1

File: plot_figure_3a.py Project: zhiru-liu/microbiome_evolution

                                bootstrap_idx]:
                            null_low_divergence_pair_counts[bootstrap_idx][
                                null_pair] = 0

                        null_low_divergence_pair_counts[bootstrap_idx][
                            null_pair] += 1

    divergence_matrices[species_name] = snp_substitution_matrix

# # low divergence strains across species
# # samples

species_names = []
sample_sizes = []

for species_name in species_phylogeny_utils.sort_phylogenetically(
        divergence_matrices.keys()):
    species_names.append(species_name)
    sample_sizes.append(divergence_matrices[species_name].shape[0])

# sort in descending order of sample size
# Sort by num haploids
#sample_sizes, species_names = zip(*sorted(zip(sample_sizes, species_names),reverse=True))

sys.stderr.write("Postprocessing %d species...\n" % len(species_names))

####################################################
#
# Set up Figure (1 panels, arranged in 1x1 grid)
#
####################################################

Example #2

File: plot_singleton_distribution.py Project: zhiru-liu/microbiome_evolution

                closest_syn_singleton_vector), numpy.array(
                    closest_syn_difference_vector), numpy.array(
                        closest_syn_opportunity_vector), numpy.array(
                            closest_non_singleton_vector), numpy.array(
                                closest_non_difference_vector), numpy.array(
                                    closest_non_opportunity_vector)

    #print numpy.array(closest_opportunity_vector)

# # low divergence strains across species
# # samples

species_names = []
sample_sizes = []

for species_name in species_phylogeny_utils.sort_phylogenetically(data.keys()):
    species_names.append(species_name)
    sample_sizes.append(len(data[species_name][0]))

# sort in descending order of sample size
# Sort by num haploids
#sample_sizes, species_names = zip(*sorted(zip(sample_sizes, species_names),reverse=True))

sys.stderr.write("Postprocessing %d species...\n" % len(species_names))

divergences = numpy.logspace(-4, -1, 10)

####################################################
#
# Set up Figure (1 panels, arranged in 1x1 grid)
#

Example #3

File: plot_figure_4.py Project: zhiru-liu/microbiome_evolution

    if len(ld_map) > 0:

        distances, rsquared_numerators, rsquared_denominators, ns, intergene_distances, intergene_rsquared_numerators, intergene_rsquared_denominators, intergene_ns, control_rsquared_numerators, control_rsquared_denominators, control_n, pi = ld_map[
            ('largest_clade', '4D')]

        if True:
            passed_species.append(species_name)
            sample_sizes.append(len(snp_samples))
        else:
            sys.stderr.write("%s intergene LD too high: %g (%g)\n" %
                             (species_name, control_rsquared, rsquareds[0]))

sample_sizes = numpy.array(sample_sizes)

passed_species = species_phylogeny_utils.sort_phylogenetically(
    passed_species,
    first_entry=focal_speciess[0],
    second_sorting_attribute=(-1 * sample_sizes))

#passed_species = species_phylogeny_utils.sort_phylogenetically(passed_species)
num_passed_species = len(passed_species)

inconsistency_axis.plot([1], [-1],
                        '-',
                        color=focal_colors[0],
                        linewidth=1,
                        alpha=1,
                        label=figure_utils.get_pretty_species_name(
                            focal_speciess[0], include_number=False))
inconsistency_axis.plot([1], [-1],
                        '-',
                        color=focal_colors[1],

Example #4

File: plot_figure_2.py Project: zhiru-liu/microbiome_evolution

# # low divergence strains across species
# # samples

species_names = []
sample_sizes = []

for species_name in divergence_matrices.keys():
    species_names.append(species_name)

    if species_name == 'Bacteroides_vulgatus_57955':
        sample_sizes.append(-1000)
    else:
        sample_sizes.append(-divergence_matrices[species_name].shape[0])

sorted_species_names = species_phylogeny_utils.sort_phylogenetically(
    divergence_matrices.keys(),
    first_entry='Bacteroides_vulgatus_57955',
    second_sorting_attribute=sample_sizes)

species_names = []
sample_sizes = []
for species_name in reversed(sorted_species_names):
    species_names.append(species_name)
    sample_sizes.append(divergence_matrices[species_name].shape[0])

# sort in descending order of sample size
# Sort by num haploids
#sample_sizes, species_names = zip(*sorted(zip(sample_sizes, species_names),reverse=True))

sys.stderr.write("Postprocessing %d species...\n" % len(species_names))
print "Analyzing %d species with %d or more QP samples" % (len(species_names),
                                                           min_sample_size)

Example #5

File: plot_figure_4 (Benjamin’s iMac's conflicted copy 2018-09-11).py Project: zhiru-liu/microbiome_evolution

    ld_map = calculate_linkage_disequilibria.load_ld_map(species_name)

    if len(ld_map) > 0:

        distances, rsquared_numerators, rsquared_denominators, ns, intergene_distances, intergene_rsquared_numerators, intergene_rsquared_denominators, intergene_ns, control_rsquared_numerators, control_rsquared_denominators, control_n, pi = ld_map[
            ('largest_clade', '4D')]

        if True:
            passed_species.append(species_name)
            sample_sizes.append(len(snp_samples))
        else:
            sys.stderr.write("%s intergene LD too high: %g (%g)\n" %
                             (species_name, control_rsquared, rsquareds[0]))

sorted_species_names = species_phylogeny_utils.sort_phylogenetically(
    passed_species,
    first_entry='Bacteroides_vulgatus_57955',
    second_sorting_attribute=sample_sizes)

#passed_species = species_phylogeny_utils.sort_phylogenetically(passed_species)
num_passed_species = len(passed_species)

inconsistency_axis.plot([1], [-1],
                        'b-',
                        linewidth=1,
                        alpha=1,
                        label=focal_species)
inconsistency_axis.plot([1], [-1],
                        'r-',
                        linewidth=0.5,
                        alpha=0.3,
                        label='Other species')