code: def fetch_hogg2010test(structured=False):
      """Fetch the Hogg et al 2010 test data"""
      data = np.array(
          [
              [1, 201, 592, 61, 9, -0.84],
              [2, 244, 401, 25, 4, 0.31],
              [3, 47, 583, 38, 11, 0.64],
              [4, 287, 402, 15, 7, -0.27],
              [5, 203, 495, 21, 5, -0.33],
              [6, 58, 173, 15, 9, 0.67],
              [7, 210, 479, 27, 4, -0.02],
              [8, 202, 504, 14, 4, -0.05],
              [9, 198, 510, 30, 11, -0.84],
              [10, 158, 416, 16, 7, -0.69],
              [11, 165, 393, 14, 5, 0.30],
              [12, 201, 442, 25, 5, -0.46],
              [13, 157, 317, 52, 5, -0.03],
              [14, 131, 311, 16, 6, 0.50],
              [15, 166, 400, 34, 6, 0.73],
              [16, 160, 337, 31, 5, -0.52],
              [17, 186, 423, 42, 9, 0.90],
              [18, 125, 334, 26, 8, 0.40],
              [19, 218, 533, 16, 6, -0.78],
              [20, 146, 344, 22, 5, -0.56],
          ]
      )
      dtype = [
          ("ID", np.int32),
          ("x", np.float64),
          ("y", np.float64),
          ("sigma_x", np.float64),
          ("sigma_y", np.float64),
          ("rho_xy", np.float64),
      ]
  
      recarray = np.empty(data.shape[0], dtype=dtype)
      recarray["ID"] = data[:, 0]
      recarray["x"] = data[:, 1]
      recarray["y"] = data[:, 2]
      recarray["sigma_x"] = data[:, 4]
      recarray["sigma_y"] = data[:, 3]
      recarray["rho_xy"] = data[:, 5]
  
      return recarray
  
label_desc: Use image node_id 1 for calling a global function with example usage: fetch_hogg2010test(structured) and returns: recarray