get_factor_variance() returns ndarray which is not ordered by variance.

When i print the variance of the factors with get_factor_variance(), the variance is not monotonically decreasing. In my understanding each additional factor should explain less and less variance. The variance of my 15 factors looks like this (notice the values marked in bold):
[12.69, 5.32, 2.7, 2.6, 2.26, 2.08, 1.76, **2.54**, **2.4**, 1.69, 1.49, **2.06**, 1.16, 1.15, **1.45**]

````
n_factors = 15
fa = FactorAnalyzer(n_factors, rotation="varimax", method='principal', use_smc=True)
fa.fit(X)
print(pd.DataFrame(fa.get_factor_variance(),index=['Variance (sum of squared loadings)','Proportional Var','Cumulative Var']))
````
I cannot provide you with the data X

Expected behavior: the output should be sorted by decreasing variance

- OS: macOS
- Python: 3.11
- Versions for `factor_analyzer` / `numpy` / `scipy` / `pandas`: newest

Start at the get_factor_variance() entry point and inspect how factor variance is calculated and ordered. Use the issue's FactorAnalyzer example with a local dataset to reproduce the non-monotonic output; done means the returned variance values decrease while the proportional and cumulative rows remain consistent.

Written by the indexing model from the issue text.