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()