code: def generate_data(path):
      distributions = {
          "Gaussian": {
              "options": dict(loc=0, scale=0.1),
              "name": "norm",
          },
          "Exponential": {
              "options": dict(loc=-0.5, scale=1),
              "name": "expon",
          },
          "Chi Square": {
              "options": dict(loc=-0.5, df=1),
              "name": "chi2",
          },
          "Alpha": {"options": dict(a=3, loc=-0.5), "name": "alpha"},
          "Beta": {"options": dict(a=3, b=2, loc=-0.5), "name": "beta"},
      }
      x = np.linspace(-1, 1, num=1000)
      with h5py.File(join(path, "demo_data.hdf5"), "w") as f:
          for group, vals in distributions.items():
              gauss_pdf = f.create_group(group)
              gauss_pdf.create_dataset("x", data=x)
              gauss_pdf.create_dataset(
                  "pdf",
                  data=getattr(ss, vals["name"])(**vals["options"]).pdf(
                      x
                  ),
              )
  
imports: from os.path import join
  import h5py
  import numpy
  import scipy.stats
label_desc: Use image node_id 1 for calling a global function with example usage: generate_data(path) without return types