eta = np.linspace(0.01,1,500)
rfast = eta / (2*eta - 1)
rfast[rfast < 0] = np.nan
rslow = 1/eta
fig = plt.figure(figsize=(6,4))
ax = fig.add_subplot(111)
ax.set_xlim(0, 100)
ax.set_ylim(1, 100)
ax.set_xlabel(r'SFE (%)', fontsize=14)
ax.set_ylabel(r'$R_{\rm final}/R_{\rm initial}$', fontsize=14)
ax.set_yscale('log')
ax.plot(100*eta, rfast, color='black', lw=2, ls='-')
ax.plot(100*eta, rslow, color='black', lw=2, ls='-')
ax.plot([50,50], [1,100], color='black', lw=1, ls=':')
ax.text(62, 3, 'fast', fontsize=12)
ax.text(13, 9, 'slow', fontsize=12)
x_labels = ['0','25','50', '75', '100']
x_loc = np.array([float(x) for x in x_labels])
ax.set_xticks(x_loc)
ax.set_xticklabels(x_labels)
y_labels = ['1','10','100']
y_loc = np.array([float(y) for y in y_labels])
ax.set_yticks(y_loc)
ax.set_yticklabels(y_labels)
fig.tight_layout()
plt.savefig('cluster_expansion.pdf')