Add smoking test

tests/why_test.py

@@ -42,6 +42,11 @@ def _validate_it(why, test_data, check_score=True):
         print("rloss:", score)
 
 
+def test_smoke():
+    from ylearn.api.smoke import smoke
+    smoke()
+
+
 def test_basis():
     data, test_data, outcome, treatment, adjustment, covariate = _dgp.generate_data_x1b_y1()
     why = Why()

ylearn/api/smoke.py

@@ -0,0 +1,35 @@
+from ylearn.api import Why
+from ylearn.exp_dataset.exp_data import single_binary_treatment
+
+
+def smoke(estimator='auto'):
+    print('-' * 20, 'smoke with estimator', estimator, '-' * 20)
+
+    train, val, _ = single_binary_treatment()
+    te = train.pop('TE')
+    te = val.pop('TE')
+    adjustment = [c for c in train.columns.tolist() if c.startswith('w')]
+    covariate = [c for c in train.columns.tolist() if c.startswith('c')]
+
+    if estimator == 'grf':
+        covariate.extend(adjustment)
+        adjustment = None
+
+    why = Why(estimator=estimator)
+    why.fit(train, outcome='outcome', treatment='treatment', adjustment=adjustment, covariate=covariate)
+
+    cate = why.causal_effect(val)
+    print('CATE:\n', cate)
+
+    auuc = why.score(val, scorer='auuc')
+    print('AUUC', auuc)
+
+
+if __name__ == '__main__':
+    from ylearn.utils import logging
+
+    logging.set_level('info')
+    for est in ['slearner', 'tlearner', 'xlearner', 'dr', 'dml', 'tree', 'grf']:
+        smoke(est)
+
+    print('\n<done>')