for ligand in ligands
]
markercolors = ["k" for ligand in ligands]
if len(x) > 1:
scatter_plot_info(x, y, ligands, out_text_file)
scatter_plot(x,
y,
args.xlabel,
args.ylabel,
out_figure_file,
show_xy_axes=args.show_xy_axes,
xerr=xerr,
yerr=yerr,
show_regression_line=True,
show_diagonal_line=False,
show_rmse=True,
show_R=True,
show_regression_line_eq=True,
markers=markers,
markersize=5,
markercolors=markercolors,
same_xy_scale=False,
text_pos=[0.1, 0.7])
all_ligands = [
all_algdock_scores[scheme][ref_ligand].keys()
for scheme in weighting_schemes for ref_ligand in SIX_YANK_SYSTEMS
]
common_ligands = set(all_ligands[0])
unioned_ligands = set(all_ligands[0])
out_file = os.path.basename(data_file) + ".pdf"
title = os.path.basename(data_file)
if args.title:
title = " vs ".join(title.split("_vs_"))
else:
title = None
scatter_plot(x,
y,
args.xlabel,
args.ylabel,
out_file,
show_xy_axes=True,
xerr=None,
yerr=None,
x_logscale=False,
y_logscale=False,
show_regression_line=False,
show_diagonal_line=False,
show_rmse=True,
show_R=True,
show_regression_line_eq=True,
markers=None,
markersize=4,
markercolors=None,
same_xy_scale=False,
integer_limits=False,
text_pos=[0.1, 0.7],
title=title)
y_errs.append(algdock_errors[ref_ligand][target_ligand])
ys = np.array(ys)
y_errs = np.array(y_errs) * error_scales[i] / 2.
dummy_ligands = ["abc" for _ in ys]
scatter_plot_info(xs, ys, dummy_ligands, out_log)
ylim = ylims[i]
if ylim is not None:
ylim = [float(s) for s in ylim.split("_")]
scatter_plot(xs,
ys,
args.xlabel,
args.ylabel,
out_fig,
show_xy_axes=True,
yerr=y_errs,
ylimits=ylim,
show_regression_line=True,
show_diagonal_line=False,
show_rmse=True,
show_R=True,
show_regression_line_eq=True,
markersize=4,
same_xy_scale=False,
text_pos=[0.1, 0.7])
print("DONE")
for target_ligand in target_ligands:
ys.append(rbfes_without_cv[ref_ligand][target_ligand])
y_errs.append(rbfe_errors_without_cv[ref_ligand][target_ligand])
ys = np.array(ys)
y_errs = np.array(y_errs) / 2.
dummy_ligands = ["abc" for _ in ys]
scatter_plot_info(xs, ys, dummy_ligands, "rmse_pearsonR_without_CV.dat")
scatter_plot(xs, ys, args.xlabel, args.ylabel, "without_CV.pdf",
show_xy_axes=True,
xerr=x_errs, yerr=y_errs,
show_regression_line=True,
show_diagonal_line=False,
show_rmse=True,
show_R=True,
show_regression_line_eq=True,
markersize=4,
same_xy_scale=False,
text_pos=[0.1, 0.7])
# with CV
ys = []
y_errs = []
for ref_ligand in ref_ligands:
for target_ligand in target_ligands:
ys.append(rbfes_with_cv[ref_ligand][target_ligand])
y_errs.append(rbfe_errors_with_cv[ref_ligand][target_ligand])