Make intehritence from base.

Author: ilan-gold

diffxpy/testing/det.py

@@ -468,17 +468,17 @@ class DifferentialExpressionTestLRT(_DifferentialExpressionTestSingle):
 
     sample_description: pd.DataFrame
     full_design_loc_info: patsy.design_info
-    full_estim: glm.train.numpy.glm_nb.Estimator
+    full_estim: glm.train.numpy.glm_base.Estimator
     reduced_design_loc_info: patsy.design_info
-    reduced_estim: glm.train.numpy.glm_nb.Estimator
+    reduced_estim: glm.train.numpy.glm_base.Estimator
 
     def __init__(
             self,
             sample_description: pd.DataFrame,
             full_design_loc_info: patsy.design_info,
-            full_estim: glm.train.numpy.glm_nb.Estimator,
+            full_estim: glm.train.numpy.glm_base.Estimator,
             reduced_design_loc_info: patsy.design_info,
-            reduced_estim: glm.train.numpy.glm_nb.Estimator
+            reduced_estim: glm.train.numpy.glm_base.Estimator
     ):
         super().__init__()
         self.sample_description = sample_description

diffxpy/unit_test/test_acc_glm_all_numpy_temp.py

@@ -9,17 +9,14 @@
 logger = logging.getLogger(__name__)
 
 
-class TestAccuracyGlmNb(
+class TestConvergence(
     unittest.TestCase
 ):
     """
     Test whether optimizers yield exact results for negative binomial distributed data.
     """
 
-    def test_full_nb(self):
-        logging.getLogger("batchglm").setLevel(logging.INFO)
-        logger.error("TestAccuracyGlmNb.test_full_nb()")
-
+    def _test_full_model(self, noise_model):
         np.random.seed(1)
         adata = sc.datasets.pbmc3k()
         tf = "MALAT1"
@@ -37,11 +34,15 @@ def test_full_nb(self):
             quick_scale=False,
             init_a="all_zero",
             size_factors=None,
-            noise_model="nb",
+            noise_model=noise_model,
             backend="numpy"
         )
         _ = temp.summary()
 
+    def test(self):
+        for noise_model in ['norm', 'poisson', 'nb']:
+            self._test_full_model(noise_model)
+
 
 if __name__ == '__main__':
     unittest.main()