[PyPortfolioOpt] Upgrade HRPOpt to prefer supplied covariance matrix

**Is your feature request related to a problem?** I was looking at the source code for `HRPOpt` and noticed that it prefers to compute the covariance as opposed to using the constructor supplied covariance matrix. I read through the earlier discussion, and was reading the code because I was interested in the implementation. **Describe the feature you'd like** I believe the following change to `HRPOpt.optimize` would allow users to supply both returns and a pre-shrunk covariance matrix and get the expected results: ```python if self.cov_matrix is not None: cov = self.cov_matrix corr = risk_models.cov_to_corr(self.cov_matrix).round(6) else: corr, cov = self.returns.corr(), self.returns.cov() ``` I'm testing out this change locally and if I can get all your unit tests to pass I'd like to submit a pull request.