db = pd.DataFrame.from_dict(t_c_p_d)
sns.barplot(x="Protein", y="Contacts", hue="Drug", data = db)
plt.savefig(os.path.join(options.results, "total_contacts.svg"))
# PLOT CONTACTS PER RESIDUE
f, axes = plt.subplots(len(proteins), len(drugs), sharey='row')
f.subplots_adjust(hspace=0.3, wspace=0.1 )
f.set_size_inches(9, 18, forward=True)
colors = sns.color_palette("hls", 15)
for i, protein in enumerate(proteins):
for j, drug in enumerate(drugs):
contacts_per_cluster = data["contacts_per_cluster"][protein][drug]
contact_residue_labels = get_labels(contacts_per_cluster)
weight = num_atoms_per_drug[drug]*frames_per_prot_drug[protein][drug]
filtered_contact_residue_labels = filter_less_contacts_than(THRESHOLD,
contact_residue_labels,
data["contacts_per_residue"][protein][drug])
plot_histogram_to_axis(axes[i,j],
protein, drug, contacts_per_cluster,
filtered_contact_residue_labels,
colors, weight, False)
axes[i,j].xaxis.grid()
axes[i,j].set_aspect("auto")
if i == 0:
axes[i,j].set_title(drug)
if j == 0:
axes[i,j].set_ylabel(protein)
axes[i,j].autoscale(tight=True)
scale_axes_to_max_val(axes, len(proteins), len(drugs))
plt.savefig(os.path.join(options.results, "contacts_per_residue_and_cluster_histogram.svg"))
def test_filter(self):
_, contacts_per_residue = histogram.parse_contacts(TestDataManaging.small_contacts_file_name)
ordered_labels = ['181:TYR:A', '266:GLY:A', '268:ASP:A', '329:ARG:A', '333:GLN:A', '337:TYR:A', '340:ASN:A', '395:ASP:A', '421:LYS:A', '442:SER:A', '461:ARG:A', '527:TRP:A', '528:SER:A']
filtered_labels = filter_less_contacts_than( 15, ordered_labels, contacts_per_residue)
self.assertItemsEqual(['266:GLY:A', '395:ASP:A', '442:SER:A', '528:SER:A'], filtered_labels)
residues_file.write("%s %s \n"%(cluster_id, " ".join(residues)))
contacts_per_cluster[cluster_id] = residues
residues_file.close()
if options.do_plots:
#--------------------------------
# Plot distribution of the residues
#--------------------------------
contacts_per_residue = get_num_contacts_per_residue(contacts_per_cluster)
contact_residue_labels = get_labels (contacts_per_cluster)
# A normal plot
target = os.path.join(RESULTS_PATH, "histogram.svg")
plot_histogram(contacts_per_cluster, contact_residue_labels, target, False)
# A plot averaging
target = os.path.join(RESULTS_PATH, "histogram_a.svg")
plot_histogram(contacts_per_cluster, contact_residue_labels, target, True)
# A plot filtering
filtered_contact_residue_labels = filter_less_contacts_than(2000, contact_residue_labels, contacts_per_residue)
target = os.path.join(RESULTS_PATH, "histogram_f.svg")
plot_histogram(contacts_per_cluster, filtered_contact_residue_labels, target, False)
# A plot filtering + averaging
filtered_contact_residue_labels = filter_less_contacts_than(2000, contact_residue_labels, contacts_per_residue)
target = os.path.join(RESULTS_PATH, "histogram_fa.svg")
plot_histogram(contacts_per_cluster, filtered_contact_residue_labels, target, True)
