e04c172ab20810a79e15949a1b1a061e540b780c,scipy/stats/kde.py,gaussian_kde,_compute_covariance,#gaussian_kde#,558

Before Change

        self.covariance = self._data_covariance * self.factor**2
        self.inv_cov = self._data_inv_cov / self.factor**2
        self._norm_factor = sqrt(linalg.det(2*pi*self.covariance))

    def pdf(self, x):
        
        Evaluate the estimated pdf on a provided set of points.

After Change

        self.covariance = self._data_covariance * self.factor**2
        self.inv_cov = self._data_inv_cov / self.factor**2
        L = linalg.cholesky(self.covariance*2*pi)
        self.log_det = 2*np.log(np.diag(L)).sum()

    def pdf(self, x):
        
        Evaluate the estimated pdf on a provided set of points.

Instances