def test_calc_prot_drug_contacts_per_motif(self):
contacts_per_cluster, _ = histogram.parse_contacts(TestDataManaging.small_contacts_file_name)
motifs = parse_motifs(os.path.join(Test.__path__[0], "data", "motifs.txt"))
ordered_motifs = ['F/I-II', 'A/IV', 'B/V', 'C/VI', 'D', 'E/VII', 'Priming Loop']
prot_drug_contacts_per_motif = calc_contacts_per_cluster_per_motif(contacts_per_cluster,
motifs["WNV"],
ordered_motifs,
1.)
correct_prot_drug_contacts_per_motif = {
'cluster_8': {'F/I-II': 4.0, 'B/V': 2.0},
'cluster_6': {'A/IV': 2.0, 'B/V': 4.0, 'Priming Loop': 4.0},
'cluster_7': {'A/IV': 15.0, 'Priming Loop': 1.0},
'cluster_4': {'C/VI': 6.0, 'Priming Loop': 4.0, 'B/V': 6.0},
'cluster_5': {'E/VII': 6.0},
'cluster_2': {'C/VI': 4.0, 'D': 5.0, 'Priming Loop': 3.0},
'cluster_3': {'Priming Loop': 6.0, 'B/V': 7.0},
'cluster_0': {'C/VI': 7.0, 'E/VII': 7.0, 'Priming Loop': 2.0},
'cluster_1': {'E/VII': 2.0, 'A/IV': 10.0, 'Priming Loop': 1.0, 'D': 2.0}
}
self.assertDictEqual(correct_prot_drug_contacts_per_motif, prot_drug_contacts_per_motif)
correct_contacts_per_motif = {
'F/I-II': 4.,
'A/IV': 27.,
'B/V': 19.,
'C/VI': 17.,
'D': 7.,
'E/VII': 15.,
'Priming Loop': 21.
}
contacts_per_motif = calc_contacts_per_motif(correct_prot_drug_contacts_per_motif, ordered_motifs)
self.assertDictEqual(correct_contacts_per_motif,contacts_per_motif)
plt.savefig(os.path.join(options.results, "contacts_per_residue_histogram.svg"),
bbox_extra_artists=(lgd,))
# COMBO HISTOGRAMS PER MOTIF
f, axes = plt.subplots(3, 2, sharey='row')
f.subplots_adjust(hspace=0.4, wspace=0.1 )
f.set_size_inches(10, 18, forward=True)
for i, protein in enumerate(proteins):
n_groups = len(ordered_motifs)
bar_width = 0.30
index = numpy.arange(n_groups) + bar_width/2
legend_labels = []
# remove "cluster_id" info
for j, drug in enumerate(drugs):
contacts_per_motif = calc_contacts_per_motif(contacts_per_motif_and_cluster[protein][drug], ordered_motifs)
values = data["contacts_per_residue"][protein][drug]
weight = num_atoms_per_drug[drug]*frames_per_prot_drug[protein][drug]
x = numpy.array([ float(contacts_per_motif[motif]) for motif in ordered_motifs])
rects = axes[i/2,i%2].bar(index, x, bar_width, color = colors[j])
index = index + bar_width
legend_labels.append(drug)
if i==3:
lgd = axes[i/2,i%2].legend(legend_labels, loc='center right', bbox_to_anchor=(1.3, 0.5))
axes[i/2,i%2].xaxis.grid()
axes[i/2,i%2].set_title(protein)
axes[i/2,i%2].set_xticklabels(ordered_motifs, rotation= 45)
axes[i/2,i%2].set_xticks(numpy.arange(n_groups)+bar_width/2)
# axes[i/2,i%2].autoscale(tight=True)
scale_axes_to_max_val(axes, 3, 2)
plt.savefig(os.path.join(options.results, "contacts_per_motif_histogram.svg"),
