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Copy pathwavefunction.py
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84 lines (57 loc) · 2 KB
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####Codi wavefunction.py per calcular els valors propis####
#Llibreries
import numpy as np
#Funcio wavefunction
#d ........... Valors de potencial
#h ........... Pas de discretitzacio
#n ........... Dimensio de la matriu
#vp .......... Valor propi determinat
def wavefunction(d,h,n,vp):
#Constants i variables
wf = np.zeros(n)
h2 = h*h
#Recalculem la diagonal
for k in xrange(1,n+1):
d[k-1] = (d[k-1] - vp)*h2 + 2
#Ajust per arrodoniments intolerables
#Punt de trobada de la integracio
nmed = n/2 + 2
#Integracio d'esquerra a dreta
wf[0] = 1.0
wf[1] = d[0]
norsum = 1 + d[0]**2
for k in xrange(3,nmed+1):
wf[k-1] = d[k-2]*wf[k-2] - wf[k-3]
norsum = norsum + wf[k-1]**2
#Preveu overflows: aplica reescalament
if (abs(wf[k-1]) >= 1e15):
for i in xrange(1,k+1):
wf[i-1] = wf[i-1]/1e15
norsum = norsum/1e30
#Evita overflows en el factor d'igualacio
if (abs(wf[nmed-1]) < 1e-12): nmed = nmed - 1
#Integracio de dreta a esquerra
wf[n-1] = 1.0
wf[n-2] = d[n-1]
for k in xrange(n-2,nmed,-1):
wf[k-1] = d[k]*wf[k] - wf[k+1]
if (abs(wf[k-1]) >= 1e15):
for i in xrange(n,k-1,-1):
wf[i-1] = wf[i-1]/1e15
#Igualar dos trossos (calculem wf[nmed] amb wf[nmed+1] i wf[nmed + 2])
wwf = d[nmed]*wf[nmed] - wf[nmed+1]
#Factor d'igualacio
fac = wf[nmed-1]/wwf
#Reconstruim el interval de dalt i completem normalitzacio
for k in xrange(nmed+1,n+1):
wf[k-1] = wf[k-1]*fac
norsum = norsum + wf[k-1]**2
#Normalitzacio de les funcions d'ona (trapezoidal)
xnorm = np.sqrt(1.0/(h*norsum))
for k in xrange(1,n+1):
wf[k-1] = xnorm*wf[k-1]
#Recompondre la diagonal
h2=h*h
for k in xrange(1,n+1):
d[k-1] = vp + (d[k-1] - 2)/h2
return wf