vmax_es = max(abs(pred_sim[0].min()), abs(pred_sim[0].max()),
abs(pred_exp[0].min()), abs(pred_exp[0].max()))
data_lims_es = (-vmax_es, vmax_es)
data_lims_hm = (min(pred_sim[1].min(), pred_exp[1].min()),
max(pred_sim[1].max(), pred_exp[1].max()) - 0.15)
# Set contour line levels to plot
levels_sim = [0.3, 0.6, 0.9, 1.2, 1.4, 1.53, 1.63, 1.75]
levels_exp = [0.3, 0.6, 0.9, 1.2, 1.4, 1.53, 1.63, 1.71]
# Plot simulation prediction
vis.plot_ES_contour(pred_sim_ax,
pred_sim[0][0],
pred_sim[1][0],
data_lims_es=data_lims_es,
data_lims_hm=data_lims_hm,
levels=levels_sim,
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
# Plot experimental prediction
vis.plot_ES_contour(pred_exp_ax,
pred_exp[0][0],
pred_exp[1][0],
data_lims_es=data_lims_es,
data_lims_hm=data_lims_hm,
levels=levels_exp,
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
horizontalalignment='center',
verticalalignment='center',
transform=input_axes[i, 0].transAxes,
rotation='vertical',
fontsize=fontsize)
# Overlay molecule geometry onto first AFM image
xyz_img = np.flipud(imageio.imread(f'images/{molecules[ib][5:-4]}.png'))
input_axes[0, 0].imshow(xyz_img,
origin='lower',
extent=ims[0].get_extent())
# Plot predictions
vis.plot_ES_contour(pred_Cl_CO_ax,
pred_Cl_CO[0][0],
pred_Cl_CO[1][0],
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
vis.plot_ES_contour(pred_Xe_Cl_ax,
pred_Xe_Cl[0][0],
pred_Xe_Cl[1][0],
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
# Set titles for first row of images
if ib == 0:
input_axes[0, len(X_slices) // 2].set_title('AFM simulation',
fontsize=fontsize)
pred_Cl_CO_ax.set_title('Prediction (Cl-CO)', fontsize=fontsize)
pred_Xe_Cl_ax.set_title('Prediction (Cl-Xe)', fontsize=fontsize)
pred_ptcda = model_ptcda.predict(X_ptcda)
# Make figure
width_ratios = [4, 4, 4.5]
gridspec_kw = {'width_ratios': width_ratios, 'wspace': 0.3}
fig, (ax_sim, ax_bcb, ax_ptcda) = plt.subplots(1,
3,
figsize=(sum(width_ratios),
2.6),
gridspec_kw=gridspec_kw)
# Plot simulation
plt.axes(ax_sim)
cbar, _ = vis.plot_ES_contour(ax_sim,
pred_sim[0][0],
pred_sim[1][0],
es_colorbar=True,
hm_colorbar=False,
axis_off=True)
cbar.set_ticks([-0.2, -0.1, 0.0, 0.1, 0.2])
# cbar.set_ticklabels([f'{i:.2f}'.replace('-', '$-$') for i in cbar.get_ticks()])
cbar.ax.tick_params(labelsize=fontsize - 4)
cbar.set_label('V/Å', fontsize=fontsize
) # Seems to be broken in matplotlib 3.3.3 with cmr10 font
# Plot BCB
plt.axes(ax_bcb)
cbar, _ = vis.plot_ES_contour(ax_bcb,
pred_bcb[0][0],
pred_bcb[1][0],
es_colorbar=True,
hm_colorbar=False,
(ptcda_axes, X_ptcda, pred_ptcda, 'PTCDA')]:
# Loop over distances
for i in range(len(X[0])):
# Plot AFM
for j, x in enumerate(X):
for k, s in enumerate(X_slices):
ax = axes[i, j * len(X_slices) + k]
im = ax.imshow(x[i, :, :, s].T, origin='lower', cmap='afmhot')
ax.set_axis_off()
# Plot predictions
vis.plot_ES_contour(axes[i, -1],
pred[0][i],
pred[1][i],
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
# Set titles
p0 = axes[0, 0].get_position().get_points()
p1 = axes[-1, 0].get_position().get_points()
plt.text(p1[0][0] - 0.016, (p1[0][1] + p0[1][1]) / 2,
title,
fontsize=fontsize,
transform=fig.transFigure,
horizontalalignment='center',
verticalalignment='center',
rotation='vertical')
px = [p0[0][0] - 0.005, p1[0][0] - 0.005]
py = [p0[1][1] - 0.01, p1[0][1] + 0.01]
input_axes[0, 0].imshow(xyz_img,
origin='lower',
extent=ims[0].get_extent())
# Figure out data limits
vmax = max(abs(pred[0].min()), abs(pred[0].max()), abs(Y[0].min()),
abs(Y[0].max()))
data_lims_es = (-vmax, vmax)
data_lims_hm = (min(pred[1].min(),
Y[1].min()), max(pred[1].max(), Y[1].max()))
# Plot prediction
vis.plot_ES_contour(pred_ax,
pred[0][0],
pred[1][0],
data_lims_es=data_lims_es,
data_lims_hm=data_lims_hm,
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
# Plot reference
vis.plot_ES_contour(ref_ax,
Y[0][0],
Y[1][0],
data_lims_es=data_lims_es,
data_lims_hm=data_lims_hm,
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
# Set titles for first row of images
afm_axes[i, j].set_axis_off()
# Put tip names to the left of the AFM image rows
afm_axes[i, 0].text(-0.1,
0.5,
tip_names[i],
horizontalalignment='center',
verticalalignment='center',
transform=afm_axes[i, 0].transAxes,
rotation='vertical',
fontsize=fontsize)
# Plot prediction
vis.plot_ES_contour(pred_ax,
pred[0][0],
pred[1][0],
es_colorbar=False,
hm_colorbar=False,
axis_off=True)
# Plot ES Map colorbar
plt.rcParams["font.serif"] = "cmr10"
vmax = max(abs(pred[0][0].min()), abs(pred[0][0].max()))
vmin = -vmax
m_es = cm.ScalarMappable(cmap=cm.coolwarm)
m_es.set_array([vmin, vmax])
cbar = plt.colorbar(m_es, cax=cbar_es_ax)
cbar.set_ticks([-0.05, 0.0, 0.05])
# cbar.set_ticklabels([f'{i:.2f}'.replace('-', '$-$') for i in cbar.get_ticks()])
cbar_es_ax.tick_params(labelsize=fontsize - 4)
cbar.set_label('V/Å', fontsize=fontsize
) # Seems to be broken in matplotlib 3.3.3 with cmr10 font