observablestuff = ObservableData(scan=scan,loadsuf=loadsuf,savesuf=loadsuf,
name=f"observables_frustrated")
delta = observablestuff.delta()
eta = observablestuff.eta()
E0 = observablestuff.E()
print(delta,eta,E0)
psistuff = PsiData(scan=scan,loadsuf=loadsuf,savesuf=savesuf,name=f"psivsr_frustrated",
sfile_format="pdf")
rs = psistuff.r()
psis = psistuff.psi()
psiprimes = psistuff.psiprime()
R0s = np.copy(rs[:len(rs)-10:5])
Es = np.copy(R0s)*0
for i,R0 in enumerate(R0s):
Es[i] = E(R0,rs,psis,psiprimes,delta,eta,K33,k24,Lambda,omega,gamma)
plt.plot(R0s,Es,'.')
plt.plot(R0s,E0+R0s*0,'--')
name="hermite-psivsr")
fig = plt.figure()
fig.set_size_inches(width, 3 * height)
ax1 = fig.add_subplot(3, 1, 1)
ax2 = fig.add_subplot(3, 1, 2)
ax3 = fig.add_subplot(3, 1, 3)
ax1.plot(psidata.r(), psidata.psi(), '.', label='actual')
ax1.plot(hermitedata.r(), hermitedata.psi(), '-', label='fit')
ax1.set_ylabel(r'$\psi(r)$')
ax2.plot(psidata.r(), psidata.psiprime(), '.', label='actual')
ax2.plot(hermitedata.r(), hermitedata.psiprime(), '-', label='fit')
ax2.set_ylabel(r'$\frac{d\psi}{dr}$')
ax3.plot(psidata.r(), psidata.rf_fibril(), '.', label='actual')
ax3.plot(hermitedata.r(), hermitedata.rf_fibril(), '-', label='fit')
ax3.legend(frameon=False)
ax3.set_ylabel(r'$r\times f_{\mathrm{fibril}}(r)$')
ax3.set_xlabel(r'$r$')
fig.subplots_adjust(left=0.2)
fig.savefig(psidata.psivsr_sname())
plt.show()