code: def load_IL2data():
      """
      Loads tensor of IL-2 mutein treatment responses.
      Tensor contains the signaling responses of eight different cell types to 13 IL-2 mutants.
      Dose-responses to 12 concentrations of muteins were collected at four time points for each mutant and cell type.
      Ligands include IL-2 mutants with modified receptor affinities, and in both mono- and bivalent formats.
      Useful for demonstrating execution and interpretation of non-negative CP decomposition.
  
      References
      ----------
      .. [1]  Orcutt-Jahns, B., Emmel, P. C., Snyder, E. M., Posner, C.,
              Carlson, S. M., & Meyer, A. S. (2021). Multivalency enhances the
              specificity of Fc-cytokine fusions. BioRxiv.
      """
      path_here = dirname(__file__)
      tensor = np.load(path_here + "/data/IL2_Response_Tensor.npy")
      ligands = [
          "IL2 (Mono)",
          "IL15 (Mono)",
          "WT N-term (Biv)",
          "H16N N-term (Biv)",
          "R38Q N-term (Biv)",
          "R38Q/H16N (Biv)",
          "WT N-term (Mono)",
          "H16N N-term (Mono)",
          "WT C-term (Mono)",
          "V91K C-term (Mono)",
          "R38Q N-term (Mono)",
          "F42Q N-Term (Mono)",
          "N88D C-term (Mono)",
      ]
      cells = [
          "Treg IL2Ra_hi",
          "Treg",
          "Treg IL2Ra_lo",
          "Thelper IL2Ra_hi",
          "Thelper",
          "Thelper IL2Ra_lo",
          "CD8+",
          "NK",
      ]
      times = [4, 2, 1, 0.5]
      doses = np.geomspace(84.0, 0.000474, 12)
      dims = ["ligands", "times", "doses", "cells"]
      reference = [
          "Orcutt-Jahns, B., Emmel, P. C., Snyder, E. M., Posner, C., \
                  Carlson, S. M., & Meyer, A. S. (2021). Multivalency enhances the \
                  specificity of Fc-cytokine fusions. BioRxiv."
      ]
      task = ["Non-Negative CP"]
      DESC = "This dataset includes a tensor of eight cell types' responses to 13 IL-2 muteins, at 4 different time points, and at 12 different IL-2 concentrations."
      LICENSE = """Copyright 2021 The Regents of the University of California
  
          Permission is hereby granted, free of charge, to any person obtaining a copy
          of this software and associated documentation files (the "Software"), to deal
          in the Software without restriction, including without limitation the rights
          to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
          copies of the Software, and to permit persons to whom the Software is
          furnished to do so, subject to the following conditions:
  
          The above copyright notice and this permission notice shall be included in all
          copies or substantial portions of the Software.
  
          THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
          IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
          FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
          AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
          LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
          OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
          SOFTWARE."""
  
      return Bunch(
          tensor=tl.tensor(tensor),
          ticks=[ligands, times, doses, cells],
          dims=dims,
          reference=reference,
          task=task,
          DESC=DESC,
          LICENSE=LICENSE,
      )
  
file_path: tensorly/tensorly/datasets/data_imports.py
imports: from os.path import dirname
  import numpy
  from urllib.request import urlopen
  import scipy.io
  from zipfile import ZipFile
  from io import BytesIO
  import tensorly
label_desc: Use image node_id 1 for calling a global function with example usage: load_IL2data() and returns: Bunch