Redefine n_factors as the number of uninformed factors

MLO-lab · May 30, 2024 · eb9e6a8 · eb9e6a8
1 parent f87c633
commit eb9e6a8
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Showing 3 changed files with 19 additions and 24 deletions.
diff --git a/examples/1_basic_tutorial.ipynb b/examples/1_basic_tutorial.ipynb
@@ -42,7 +42,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Using matplotlib backend: <object object at 0x7f4870dffb30>\n"
+      "Using matplotlib backend: <object object at 0x1767f3b20>\n"
      ]
     }
    ],
@@ -79,7 +79,15 @@
    "execution_count": 5,
    "id": "db044f07",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Torch not compiled with CUDA enabled\n"
+     ]
+    }
+   ],
    "source": [
     "device = \"cpu\"\n",
     "try:\n",

diff --git a/tests/test_alternative_input.py b/tests/test_alternative_input.py
@@ -16,8 +16,6 @@ def test_from_adata(pandas_input):
     mask = pandas_input["masks"][view_idx]
     cov = pandas_input["covariates"]
 
-    n_factors = mask.shape[0]
-
     adata = ad.AnnData(obs)
     adata.obsm["X_np"] = obs.iloc[:, : (obs.shape[1] // 2)].values
     adata.obsm["X_pd"] = obs.iloc[:, : (obs.shape[1] // 2)]
@@ -41,9 +39,11 @@ def test_from_adata(pandas_input):
                 if obs_key_val == "":
                     obs_key_val = None
 
+                n_factors = 0
                 prior_mask_key_val = prior_mask_key
                 if prior_mask_key_val == "":
                     prior_mask_key_val = None
+                    n_factors = mask.shape[0]
 
                 covariate_key_val = covariate_key
                 if covariate_key_val == "":
@@ -69,8 +69,6 @@ def test_from_adata(pandas_input):
 
 
 def test_from_mdata(pandas_input):
-    n_factors = pandas_input["masks"][0].shape[0]
-
     adata_dict = {}
 
     for view_idx, view_obs in enumerate(pandas_input["observations"]):
@@ -101,9 +99,11 @@ def test_from_mdata(pandas_input):
                 if obs_key_val == "":
                     obs_key_val = None
 
+                n_factors = 0
                 prior_mask_key_val = prior_mask_key
                 if prior_mask_key_val == "":
                     prior_mask_key_val = None
+                    n_factors = pandas_input["masks"][0].shape[0]
 
                 covariate_key_val = covariate_key
                 if covariate_key_val == "":

diff --git a/tests/test_prior.py b/tests/test_prior.py
@@ -1,36 +1,23 @@
 from muvi import MuVI
 
 
-def test_fewer_n_factors(pandas_input):
-    model = MuVI(
-        pandas_input["observations"],
-        pandas_input["masks"],
-        pandas_input["covariates"],
-        n_factors=pandas_input["n_factors"] - 2,
-        view_names=pandas_input["view_names"],
-        device="cpu",
-    )
-
-    assert model.n_factors == pandas_input["n_factors"]
-
-
 def test_more_n_factors(pandas_input):
-    n_dense = 2
+    n_factors = 2
 
     model = MuVI(
         pandas_input["observations"],
         pandas_input["masks"],
         pandas_input["covariates"],
-        n_factors=pandas_input["n_factors"] + n_dense,
+        n_factors=n_factors,
         view_names=pandas_input["view_names"],
         device="cpu",
     )
 
-    assert model.n_factors == pandas_input["n_factors"] + n_dense
+    assert model.n_factors == pandas_input["n_factors"] + n_factors
     assert (
-        model.factor_names[-n_dense:] == [f"dense_{k}" for k in range(n_dense)]
+        model.factor_names[-n_factors:] == [f"dense_{k}" for k in range(n_factors)]
     ).all()
 
     for prior_mask in model.get_prior_masks().values():
         assert prior_mask.shape[0] == model.n_factors
-        assert prior_mask[-n_dense:, :].all()
+        assert prior_mask[-n_factors:, :].all()