def iterate_lte_ne_eq_pops(self, atmos: Atmosphere):
atmos.nondimensionalise()
maxIter = 500
prevNe = np.copy(atmos.ne)
ne = np.copy(atmos.ne)
for it in range(maxIter):
atomicPops = []
prevNe[:] = ne
ne.fill(0.0)
for a in sorted(self.atoms, key=atomic_weight_sort):
nTotal = self.atomicTable[a.name].abundance * atmos.nHTot
nStar = lte_pops(a, atmos, nTotal, debye=True)
atomicPops.append(AtomicState(a, nStar, nTotal))
stages = np.array([l.stage for l in a.levels])
# print(stages)
ne += np.sum(nStar * stages[:, None], axis=0)
# print(ne)
atmos.ne[:] = ne
relDiff = np.nanmax(np.abs(1.0 - prevNe / ne))
print(relDiff)
maxRelDiff = np.nanmax(relDiff)
if maxRelDiff < 1e-3:
print("Iterate LTE: %d iterations" % it)
break
else:
print("LTE ne failed to converge")
atmos.dimensionalise()
table = AtomicStateTable(atmos, self.atomicTable, atomicPops)
return table
def update_nTotal(self, atmos : Atmosphere):
dim = False
if atmos.dimensioned:
dim = True
atmos.nondimensionalise()
self.nTotal[:] = self.model.atomicTable[self.name].abundance * atmos.nHTot
if dim:
atmos.dimensionalise()