docs: def hsolve(A, y):
      r"""Solver for the linear equations of two variables and equations only.
  
      It uses Householder reductions to solve ``Ax = y`` in a robust manner.
  
      Parameters
      ----------
      A : array_like
          Coefficient matrix.
      y : array_like
          Ordinate values.
  
      Returns
      -------
      :class:`numpy.ndarray`  Solution ``x``.
      """
  
      n = _norm(A[0, 0], A[1, 0])
      u0 = A[0, 0] - n
      u1 = A[1, 0]
      nu = _norm(u0, u1)
  
      with errstate(invalid="ignore", divide="ignore"):
          v0 = nan_to_num(u0 / nu)
          v1 = nan_to_num(u1 / nu)
  
      B00 = 1 - 2 * v0 * v0
      B01 = 0 - 2 * v0 * v1
      B11 = 1 - 2 * v1 * v1
  
      D00 = B00 * A[0, 0] + B01 * A[1, 0]
      D01 = B00 * A[0, 1] + B01 * A[1, 1]
      D11 = B01 * A[0, 1] + B11 * A[1, 1]
  
      b0 = y[0] - 2 * y[0] * v0 * v0 - 2 * y[1] * v0 * v1
      b1 = y[1] - 2 * y[0] * v1 * v0 - 2 * y[1] * v1 * v1
  
      n = _norm(D00, D01)
      u0 = D00 - n
      u1 = D01
      nu = _norm(u0, u1)
  
      with errstate(invalid="ignore", divide="ignore"):
          v0 = nan_to_num(u0 / nu)
          v1 = nan_to_num(u1 / nu)
  
      E00 = 1 - 2 * v0 * v0
      E01 = 0 - 2 * v0 * v1
      E11 = 1 - 2 * v1 * v1
  
      F00 = E00 * D00 + E01 * D01
      F01 = E01 * D11
      F11 = E11 * D11
  
      F11 = (npy_abs(F11) > epsilon.small) * F11
  
      with errstate(divide="ignore", invalid="ignore"):
          Fi00 = nan_to_num(F00 / F00 / F00)
          Fi11 = nan_to_num(F11 / F11 / F11)
          Fi10 = nan_to_num(-(F01 / F00) * Fi11)
  
      c0 = Fi00 * b0
      c1 = Fi10 * b0 + Fi11 * b1
  
      x0 = E00 * c0 + E01 * c1
      x1 = E01 * c0 + E11 * c1
  
      return array([x0, x1])