code: def series():
      return np.array(
          [
              91.50,
              94.81,
              94.38,
              95.09,
              93.78,
              94.62,
              92.53,
              92.75,
              90.31,
              92.47,
              96.12,
              97.25,
              98.50,
              89.88,
              91.00,
              92.81,
              89.16,
              89.34,
              91.62,
              89.88,
              88.38,
              87.62,
              84.78,
              83.00,
              83.50,
              81.38,
              84.44,
              89.25,
              86.38,
              86.25,
              85.25,
              87.12,
              85.81,
              88.97,
              88.47,
              86.88,
              86.81,
              84.88,
              84.19,
              83.88,
              83.38,
              85.50,
              89.19,
              89.44,
              91.09,
              90.75,
              91.44,
              89.00,
              91.00,
              90.50,
              89.03,
              88.81,
              84.28,
              83.50,
              82.69,
              84.75,
              85.66,
              86.19,
              88.94,
              89.28,
              88.62,
              88.50,
              91.97,
              91.50,
              93.25,
              93.50,
              93.16,
              91.72,
              90.00,
              89.69,
              88.88,
              85.19,
              83.38,
              84.88,
              85.94,
              97.25,
              99.88,
              104.94,
              106.00,
              102.50,
              102.41,
              104.59,
              106.12,
              106.00,
              106.06,
              104.62,
              108.62,
              109.31,
              110.50,
              112.75,
              123.00,
              119.62,
              118.75,
              119.25,
              117.94,
              116.44,
              115.19,
              111.88,
              110.59,
              118.12,
              116.00,
              116.00,
              112.00,
              113.75,
              112.94,
              116.00,
              120.50,
              116.62,
              117.00,
              115.25,
              114.31,
              115.50,
              115.87,
              120.69,
              120.19,
              120.75,
              124.75,
              123.37,
              122.94,
              122.56,
              123.12,
              122.56,
              124.62,
              129.25,
              131.00,
              132.25,
              131.00,
              132.81,
              134.00,
              137.38,
              137.81,
              137.88,
              137.25,
              136.31,
              136.25,
              134.63,
              128.25,
              129.00,
              123.87,
              124.81,
              123.00,
              126.25,
              128.38,
              125.37,
              125.69,
              122.25,
              119.37,
              118.50,
              123.19,
              123.50,
              122.19,
              119.31,
              123.31,
              121.12,
              123.37,
              127.37,
              128.50,
              123.87,
              122.94,
              121.75,
              124.44,
              122.00,
              122.37,
              122.94,
              124.00,
              123.19,
              124.56,
              127.25,
              125.87,
              128.86,
              132.00,
              130.75,
              134.75,
              135.00,
              132.38,
              133.31,
              131.94,
              130.00,
              125.37,
              130.13,
              127.12,
              125.19,
              122.00,
              125.00,
              123.00,
              123.50,
              120.06,
              121.00,
              117.75,
              119.87,
              122.00,
              119.19,
              116.37,
              113.50,
              114.25,
              110.00,
              105.06,
              107.00,
              107.87,
              107.00,
              107.12,
              107.00,
              91.00,
              93.94,
              93.87,
              95.50,
              93.00,
              94.94,
              98.25,
              96.75,
              94.81,
              94.37,
              91.56,
              90.25,
              93.94,
              93.62,
              97.00,
              95.00,
              95.87,
              94.06,
              94.62,
              93.75,
              98.00,
              103.94,
              107.87,
              106.06,
              104.50,
              105.00,
              104.19,
              103.06,
              103.42,
              105.27,
              111.87,
              116.00,
              116.62,
              118.28,
              113.37,
              109.00,
              109.70,
              109.25,
              107.00,
              109.19,
              110.00,
              109.20,
              110.12,
              108.00,
              108.62,
              109.75,
              109.81,
              109.00,
              108.75,
              107.87,
          ]
      )
  
imports: from __future__ import print_function
  import pytest
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: series() and returns: np