code: def get_synthetic_data_linear_simple(
      model_name=None, num_groups=8, mean_boundary=1, num_duplicates=16
  ):
      assert num_groups > 1
      num_time_steps = 100
  
      dataset_group = []
      whole_data_list = []
      start = pd.Timestamp("01-01-2019", freq="1D")
      for gid in range(num_groups):
          base = np.linspace(0, 10, num_time_steps)
          pattern_group = []
          ts = (
              (gid + 1)
              * mean_boundary
              * torch.FloatTensor(base).view(1, num_time_steps)
          )
          for j in range(num_duplicates):
              ts += torch.normal(0, 0.01, size=ts.shape)
              whole_data_list.append(
                  {
                      "target": ts.view(
                          len(ts[0]),
                      ),
                      "start": start,
                  }
              )
              pattern_group.append(
                  {
                      "target": ts.view(
                          len(ts[0]),
                      ),
                      "start": start,
                  }
              )
          dataset_group.append(ListDataset(pattern_group, freq="1D"))
  
      random.shuffle(whole_data_list)
  
      dataset = ListDataset(whole_data_list, freq="1D")
      dataset_group = [dataset] + dataset_group
  
      # save to files
      with open(
          "synthetic_linear_simple_whole_data.csv", "wb"
      ) as output:
          pickle.dump(dataset, output)
  
      with open(
          "synthetic_linear_simple_group_data.csv", "wb"
      ) as output:
          pickle.dump(dataset_group, output)
      return True
  
imports: from pts.dataset.repository.datasets import get_dataset, dataset_recipes
  from pts.dataset.utils import to_pandas
  import numpy
  import pandas
  from pts.dataset import ListDataset
  import torch
  from pts.model.simple_feedforward import SimpleFeedForwardEstimator
  import pickle
  import json
  import random
label_desc: Use image node_id 13 for calling a global function with example usage: get_synthetic_data_linear_simple(model_name, num_groups, mean_boundary, num_duplicates) and returns: True