docstr: Test on synthetic dataset
          
docstr_tok: ["Test","on","synthetic","dataset"]
code: def setup(self):
      """Test on synthetic dataset"""
      np.random.seed(13)
      random.seed(13)
      self.n = 100
      self.p = 2
      self.X = (np.random.randn(self.n, self.p) > 0).astype(int)
  
      # y = x0 > 0 * x1 > 0
      self.y_classification_binary = (self.X[:, 0] > 0).astype(int) * (
          self.X[:, 1] > 0
      ).astype(int)
      self.y_reg = self.X[:, 0] + self.X[:, 1]
  
file_path: imodels/tests/figs_test.py
imports: import os
  import random
  from functools import partial
  import numpy
  import pandas
  from sklearn.tree import DecisionTreeRegressor
  from imodels import FIGSClassifier, FIGSRegressor, FIGSClassifierCV, FIGSRegressorCV
  from imodels.experimental.figs_ensembles import FIGSExtRegressor, FIGSExtClassifier
  from sklearn.ensemble import StackingRegressor, VotingRegressor, BaggingClassifier
label_desc: Use image node_id 1 for calling the TestFIGS obj's underlying member method code with example usage: obj.setup() without return types