Function resample_prices

crates/openquant/src/cla.rs:345–363

(prices: &DMatrix<f64>, step: usize)

                    return Err(ClaError::NoData);
                }
                self._initialise(prices, resample_by, expected_asset_returns, covariance_matrix)?;
            }
            None => {
                let (Some(exp), Some(cov)) = (expected_asset_returns, covariance_matrix) else {
                    return Err(ClaError::MissingInputs);
                };
                self.expected_returns = normalize_expected_returns(exp)?;
                self.cov_matrix = cov.clone_owned();
                let bounds = build_bounds(self.expected_returns.nrows(), &self.weight_bounds)?;
                self.lower_bounds = bounds.iter().map(|b| b.0).collect();
                self.upper_bounds = bounds.iter().map(|b| b.1).collect();
            }
        }
        let n = self.expected_returns.nrows();
        if self.cov_matrix.nrows() != n || self.cov_matrix.ncols() != n {
            return Err(ClaError::DimensionMismatch);
        }
        let bounds: Vec<(f64, f64)> =
            self.lower_bounds.iter().copied().zip(self.upper_bounds.iter().copied()).collect();
        check_bounds_feasible(&bounds)?;

        let mean: Vec<f64> = self.expected_returns.column(0).iter().copied().collect();