code: def _is_redundant(self, matrix, cutoff=None):
          
  
          cutoff = 1.0 - self.feasibility_tol
  
          # Avoid zero variances
          extra_col = matrix[:, 0] + 1
  
          # Avoid zero rows being correlated with constant rows
          extra_col[matrix.sum(axis=1) == 0] = 2
          corr = np.corrcoef(np.c_[matrix, extra_col])
          corr = np.tril(corr, -1)
  
          return (np.abs(corr) > cutoff).any(axis=1)
docs: Identify rdeundant rows in a matrix that can be removed.