code: def generate(self, n_samples):
      time = gs.random.rand(n_samples)
      time = time - gs.mean(time)
  
      y = self.space.metric.exp(
          gs.einsum("n,...->n...", time, self.coef), self.intercept
      )
      return time, y
  
file_path: geomstats/geomstats/test_cases/learning/geodesic_regression.py
imports: import pytest
  import geomstats.backend
  from geomstats.test.random import RandomDataGenerator
  from geomstats.test_cases.learning._base import BaseEstimatorTestCase
label_desc: Use image node_id 3 for calling the Model obj's underlying member method code with example usage: obj.generate(n_samples) and returns: time,  y