Commit ed0e94b9 authored by Studer Gabriel's avatar Studer Gabriel
Browse files

add lddt to per-model comparison plot

parent 03821d56
......@@ -101,7 +101,7 @@ def DoThingsWithAxes(ax, x_values, y_values, title, xlabel, ylabel):
elif max_val <= 30:
step_size = 5
elif max_val <= 100:
step_size = 10
step_size = 20
else:
step_size = 50
for i in range(0, int(max_val)+step_size, step_size):
......@@ -110,31 +110,37 @@ def DoThingsWithAxes(ax, x_values, y_values, title, xlabel, ylabel):
ax.set_xticks(tick_locations)
ax.set_yticks(tick_locations)
fig, axs = plt.subplots(2, 2, figsize=(7,7))
probity_overall_ax = axs[0, 0]
probity_clash_ax = axs[0, 1]
probity_rotamer_ax = axs[1, 0]
probity_ramachandran_ax = axs[1, 1]
fig, axs = plt.subplots(3, 2, figsize=(7,10.5))
lddt_ax = axs[0, 0]
probity_overall_ax = axs[0, 1]
probity_clash_ax = axs[1, 0]
probity_rotamer_ax = axs[1, 1]
probity_ramachandran_ax = axs[2, 0]
empty_ax = axs[2,1]
empty_ax.axis('off')
DoThingsWithAxes(lddt_ax, lddt_values_promod,
lddt_values_modeller, 'a) lDDT',
promod_label, modeller_label)
DoThingsWithAxes(probity_overall_ax, probity_values_promod,
probity_values_modeller, 'a) Overall Score',
probity_values_modeller, 'b) MolProbity Overall',
promod_label, modeller_label)
DoThingsWithAxes(probity_clash_ax, probity_clash_promod,
probity_clash_modeller, 'b) Clash Score',
probity_clash_modeller, 'c) MolProbity Clash',
promod_label, modeller_label)
DoThingsWithAxes(probity_rotamer_ax, probity_rotamer_outliers_promod,
probity_rotamer_outliers_modeller, 'c) Rotamer Outliers',
probity_rotamer_outliers_modeller, 'd) MolProbity Rot. Outliers',
promod_label, modeller_label)
DoThingsWithAxes(probity_ramachandran_ax, probity_ramachandran_outliers_promod,
probity_ramachandran_outliers_modeller,
'd) Ramachandran Outliers', promod_label, modeller_label)
'e) MolProbity Ram. Outliers', promod_label, modeller_label)
plt.tight_layout(pad=1.2, h_pad=1.5, w_pad=1.5, rect=None)
plt.savefig(molprobity_plot_name)
plt.savefig(molprobity_plot_name, dpi=300)
print('avg. lddt value', promod_label, np.mean(lddt_values_promod))
print('avg. lddt value', modeller_label, np.mean(lddt_values_modeller))
......
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