code: def get_train_data(n_features=10, n_samples=10000, nnz=3, seed=12):
      np.random.seed(seed)
      coeffs0 = weights_sparse_gauss(n_features, nnz=nnz)
      features, times, censoring = SimuCoxReg(
          coeffs0, verbose=False
      ).simulate()
      return features, times, censoring
  
file_path: tick/tick/survival/tests/cox_regression_test.py
imports: import unittest
  import numpy
  from tick.base.inference import InferenceTest
  from tick.survival import SimuCoxReg, CoxRegression
  from tick.simulation import weights_sparse_gauss
  from tick.preprocessing.features_binarizer import FeaturesBinarizer
  from tick.prox import ProxZero, ProxL1, ProxL2Sq, ProxElasticNet, ProxTV, ProxBinarsity
  from tick.solver import GD, AGD
label_desc: Use image node_id 1 for calling the Test obj's underlying member method code with example usage: obj.get_train_data(n_features, n_samples, nnz, seed) and returns: features,  times,  censoring