def __get_vtt_angles(self, pvals, nvals):
<EOL>angles = np.arctan2(pvals, nvals)-np.pi/<NUM_LIT:4><EOL>norm = np.maximum(np.minimum(angles, np.pi-angles), -<NUM_LIT:1>*np.pi-angles)<EOL>norm = csr_matrix(norm)<EOL>for key, value in self.B.items():<EOL><INDENT>norm[<NUM_LIT:0>, key] = <NUM_LIT:0.><EOL><DEDENT>return norm<EOL>
Fit the angles to the model

        Args:
                pvals (array-like) : positive values
                nvals (array-like) : negative values

        Returns: normalized coef_ values