c899e6e816306956208664dcabd11e5e84e4bcb7,factor_analyzer/factor_analyzer.py,FactorAnalyzer,get_factor_variance,#FactorAnalyzer#,897

Before Change

        Proportion Var  0.351019  0.128371  0.073739
        Cumulative Var  0.351019  0.479390  0.553129
        
        if self.loadings is not None:

            loadings = self.loadings

            n_rows = loadings.shape[0]

            // calculate variance
            loadings = loadings ** 2
            variance = loadings.sum(axis=0)

            // calculate proportional variance
            proportional_variance = variance / n_rows

            // calculate cumulative variance
            cumulative_variance = proportional_variance.cumsum(axis=0)

            // package variance info
            variance_info = pd.DataFrame([variance,
                                          proportional_variance,
                                          cumulative_variance],
                                         index=["SS Loadings",
                                                "Proportion Var",
                                                "Cumulative Var"])

            return variance_info

    def get_scores(self,
                   data,
                   scale_mean=None,
                   scale_std=None):

After Change

         array([0.35101885, 0.47938987, 0.55312938]))
        
        // meets all of our expected criteria
        check_is_fitted(self, "loadings_")
        loadings = self.loadings_.copy()
        return self._get_factor_variance(loadings)

Instances