improve tests

Author: lappalainenj

config/network/network.yaml

@@ -4,3 +4,4 @@ defaults:
   - dynamics: dynamics
   - edge_config: edge_config
   - node_config: node_config
+  - stimulus_config: stimulus_config

config/network/stimulus_config/stimulus_config.yaml

@@ -0,0 +1,2 @@
+type: Stimulus
+init_buffer: false

examples/01_flyvision_connectome.ipynb

@@ -152,7 +152,7 @@
                 "# This json-file includes a list of cell types (`nodes`) and average convolutional filters\n",
                 "# (anatomical receptive fields) (`edges`) that are scattered across a regular hexagonal lattice\n",
                 "# of 15 column extent and stored on the hierarchical filesystem as h5-files.\n",
-                "config = dict(file=connectome_file, extent=15, n_syn_fill=1)\n",
+                "config = dict(file=connectome_file.name, extent=15, n_syn_fill=1)\n",
                 "connectome = ConnectomeFromAvgFilters(config)"
             ]
         },

tests/conftest.py

@@ -13,7 +13,7 @@
 def connectome(tmp_path_factory):
     return ConnectomeFromAvgFilters(
         tmp_path_factory.mktemp("tmp") / "test",
-        dict(file=connectome_file, extent=1, n_syn_fill=1),
+        dict(file=connectome_file.name, extent=1, n_syn_fill=1),
     )
 
 

tests/test_paths.py

@@ -0,0 +1,75 @@
+import os
+import tempfile
+from pathlib import Path
+
+import flyvis
+
+
+def test_default_root_dir():
+    """Test that the default root directory is correctly set relative to the package."""
+    # Clear any existing FLYVIS_ROOT_DIR environment variable
+    if "FLYVIS_ROOT_DIR" in os.environ:
+        del os.environ["FLYVIS_ROOT_DIR"]
+
+    # Get the resolved root directory
+    root_dir = flyvis.resolve_root_dir()
+
+    # Expected default is repo_dir/data
+    expected_dir = flyvis.repo_dir / "data"
+    assert root_dir == expected_dir.absolute()
+
+
+def test_env_var_root_dir():
+    """Test that FLYVIS_ROOT_DIR environment variable is respected."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # Set environment variable to temp directory
+        os.environ["FLYVIS_ROOT_DIR"] = temp_dir
+
+        # Get the resolved root directory
+        root_dir = flyvis.resolve_root_dir()
+
+        assert root_dir == Path(temp_dir).absolute()
+
+
+def test_dotenv_file():
+    """Test that .env file is properly loaded."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        temp_path = Path(temp_dir)
+
+        # Create a .env file
+        env_content = f'FLYVIS_ROOT_DIR={temp_dir}'
+        with open(temp_path / '.env', 'w') as f:
+            f.write(env_content)
+
+        # Clear any existing environment variable
+        if "FLYVIS_ROOT_DIR" in os.environ:
+            del os.environ["FLYVIS_ROOT_DIR"]
+
+        # Change to temp directory and reload environment
+        original_dir = os.getcwd()
+        os.chdir(temp_dir)
+
+        try:
+            import dotenv
+
+            dotenv.load_dotenv(dotenv.find_dotenv(usecwd=True))
+
+            # Get the resolved root directory
+            root_dir = flyvis.resolve_root_dir()
+
+            assert root_dir == temp_path.absolute()
+
+        finally:
+            # Restore original directory
+            os.chdir(original_dir)
+
+
+def test_path_expansion():
+    """Test that user path expansion works correctly."""
+    test_path = "~/flyvis_test"
+    os.environ["FLYVIS_ROOT_DIR"] = test_path
+
+    root_dir = flyvis.resolve_root_dir()
+    expected_dir = Path(test_path).expanduser().absolute()
+
+    assert root_dir == expected_dir

tests/test_sintel.py

@@ -39,30 +39,31 @@ def test_rendering(mock_sintel_data, tmp_path_factory):
 
 
 @pytest.fixture(scope="module")
-def dataset(mock_sintel_data):
-    return MultiTaskSintel(
-        tasks=["flow"],
-        boxfilter=dict(extent=1, kernel_size=13),
-        vertical_splits=3,
-        n_frames=4,
-        center_crop_fraction=0.7,
-        dt=1 / 24,
-        augment=True,
-        random_temporal_crop=True,
-        all_frames=False,
-        resampling=True,
-        interpolate=True,
-        p_flip=0.5,
-        p_rot=5 / 6,
-        contrast_std=0.2,
-        brightness_std=0.1,
-        gaussian_white_noise=0.08,
-        gamma_std=None,
-        _init_cache=True,
-        unittest=True,
-        flip_axes=[0, 1, 2, 3],
-        sintel_path=mock_sintel_data,
-    )
+def dataset(mock_sintel_data, tmp_path_factory):
+    with set_root_context(tmp_path_factory.mktemp("tmp")):
+        return MultiTaskSintel(
+            tasks=["flow"],
+            boxfilter=dict(extent=1, kernel_size=13),
+            vertical_splits=3,
+            n_frames=4,
+            center_crop_fraction=0.7,
+            dt=1 / 24,
+            augment=True,
+            random_temporal_crop=True,
+            all_frames=False,
+            resampling=True,
+            interpolate=True,
+            p_flip=0.5,
+            p_rot=5 / 6,
+            contrast_std=0.2,
+            brightness_std=0.1,
+            gaussian_white_noise=0.08,
+            gamma_std=None,
+            _init_cache=True,
+            unittest=True,
+            flip_axes=[0, 1, 2, 3],
+            sintel_path=mock_sintel_data,
+        )
 
 
 @pytest.fixture(
@@ -81,25 +82,26 @@ def tasks(request):
     return request.param
 
 
-def test_init(tasks, mock_sintel_data):
-    dataset = MultiTaskSintel(
-        tasks=tasks, n_frames=4, unittest=True, sintel_path=mock_sintel_data
-    )
-    assert hasattr(dataset, "tasks")
-    assert "lum" in dataset.data_keys
-    assert hasattr(dataset, "config")
-    assert hasattr(dataset, "meta")
-    assert hasattr(dataset, "cached_sequences")
-    assert hasattr(dataset, "arg_df")
-    assert set(dataset[0].keys()) == set(["lum", *tasks])
-    dataset = MultiTaskSintel(
-        tasks=tasks,
-        n_frames=4,
-        unittest=True,
-        _init_cache=False,
-        sintel_path=mock_sintel_data,
-    )
-    assert not hasattr(dataset, "cached_sequences")
+def test_init(tasks, mock_sintel_data, tmp_path_factory):
+    with set_root_context(tmp_path_factory.mktemp("tmp")):
+        dataset = MultiTaskSintel(
+            tasks=tasks, n_frames=4, unittest=True, sintel_path=mock_sintel_data
+        )
+        assert hasattr(dataset, "tasks")
+        assert "lum" in dataset.data_keys
+        assert hasattr(dataset, "config")
+        assert hasattr(dataset, "meta")
+        assert hasattr(dataset, "cached_sequences")
+        assert hasattr(dataset, "arg_df")
+        assert set(dataset[0].keys()) == set(["lum", *tasks])
+        dataset = MultiTaskSintel(
+            tasks=tasks,
+            n_frames=4,
+            unittest=True,
+            _init_cache=False,
+            sintel_path=mock_sintel_data,
+        )
+        assert not hasattr(dataset, "cached_sequences")
 
 
 def test_init_augmentation(dataset):

tests/test_solver.py

@@ -15,11 +15,15 @@ def solver(mock_sintel_data, tmp_path_factory) -> MultiTaskSolver:
             "task.n_iters=50",
             f"+task.dataset.sintel_path={str(mock_sintel_data)}",
             "task.original_split=false",
+            "task.dataset.boxfilter.extent=1",
+            "task.dataset.n_frames=4",
+            "task.dataset.dt=0.041",
+            "task.batch_size=2",
+            "network.connectome.extent=1",
         ],
     )
     with set_root_context(str(tmp_path_factory.mktemp("tmp"))):
-        solver = MultiTaskSolver("test", config)
-    return solver
+        return MultiTaskSolver("test", config)
 
 
 def test_solver_config():

tests/test_tasks.py

@@ -1,9 +1,9 @@
-from datamate import Namespace
+from datamate import Namespace, set_root_context
 
 from flyvis.task.tasks import Task
 
 
-def test_task(mock_sintel_data, connectome):
+def test_task(mock_sintel_data, connectome, tmp_path_factory):
     task_config = Namespace(
         type="Task",
         dataset=Namespace(
@@ -50,19 +50,19 @@ def test_task(mock_sintel_data, connectome):
         train_seq_ind=None,
         val_seq_ind=None,
     )
+    with set_root_context(tmp_path_factory.mktemp("tmp")):
+        task = Task(
+            task_config.dataset,
+            task_config.decoder,
+            task_config.loss,
+            batch_size=4,
+            n_iters=250_000,
+            n_folds=4,
+            fold=1,
+            seed=0,
+        )
+        assert task is not None
+        assert task.dataset is not None
 
-    task = Task(
-        task_config.dataset,
-        task_config.decoder,
-        task_config.loss,
-        batch_size=4,
-        n_iters=250_000,
-        n_folds=4,
-        fold=1,
-        seed=0,
-    )
-    assert task is not None
-    assert task.dataset is not None
-
-    decoder = task.init_decoder(connectome)
-    assert decoder is not None
+        decoder = task.init_decoder(connectome)
+        assert decoder is not None