update: improve tests for complexity markers

juaml · Nov 14, 2023 · a12e50d · a12e50d
1 parent 7e8e2a3
commit a12e50d
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Showing 7 changed files with 127 additions and 162 deletions.
diff --git a/junifer/markers/complexity/tests/test_hurst_exponent.py b/junifer/markers/complexity/tests/test_hurst_exponent.py
@@ -1,18 +1,23 @@
 """Provide test for Hurst exponent."""
 
 # Authors: Amir Omidvarnia <[email protected]>
+#          Synchon Mandal <[email protected]>
 # License: AGPL
 
-import os
 from pathlib import Path
 
-from nilearn.maskers import NiftiLabelsMasker
+import pytest
 
-from junifer.data import load_parcellation
-from junifer.datareader import DefaultDataReader
-from junifer.markers import HurstExponent
-from junifer.storage import SQLiteFeatureStorage
-from junifer.testing.datagrabbers import SPMAuditoryTestingDatagrabber
+
+pytest.importorskip("neurokit2")
+
+
+from junifer.datareader import DefaultDataReader  # noqa: E402
+from junifer.markers.complexity import HurstExponent  # noqa: E402
+from junifer.storage import SQLiteFeatureStorage  # noqa: E402
+from junifer.testing.datagrabbers import (  # noqa: E402
+    SPMAuditoryTestingDataGrabber,
+)
 
 
 # Set parcellation
@@ -21,7 +26,7 @@
 
 def test_compute() -> None:
     """Test HurstExponent compute()."""
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
@@ -30,17 +35,8 @@ def test_compute() -> None:
         marker = HurstExponent(parcellation=PARCELLATION)
         # Compute the marker
         feature_map = marker.fit_transform(element_data)
-
-    # Load parcellation
-    test_parcellation, _, _ = load_parcellation(PARCELLATION)
-    # Compute the NiftiLabelsMasker
-    test_masker = NiftiLabelsMasker(test_parcellation)
-    test_ts = test_masker.fit_transform(element_data["BOLD"]["data"])
-    _, n_roi = test_ts.shape
-
-    # Assert the dimension of timeseries
-    _, n_roi2 = feature_map["BOLD"]["data"].shape
-    assert n_roi == n_roi2
+        # Assert the dimension of timeseries
+        assert feature_map["BOLD"]["data"].ndim == 2
 
 
 def test_get_output_type() -> None:
@@ -58,17 +54,16 @@ def test_store(tmp_path: Path) -> None:
         The path to the test directory.
 
     """
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
         element_data = DefaultDataReader().fit_transform(element)
         # Initialize the marker
         marker = HurstExponent(parcellation=PARCELLATION)
-
         # Create storage
-        # tmp_path = "/home/aomidvarnia/tmp"
-        storage_uri = os.path.join(tmp_path, "test_hurst_exponent.sqlite")
-        storage = SQLiteFeatureStorage(uri=storage_uri)
+        storage = SQLiteFeatureStorage(
+            uri=tmp_path / "test_hurst_exponent.sqlite"
+        )
         # Compute the marker and store
         marker.fit_transform(input=element_data, storage=storage)
diff --git a/junifer/markers/complexity/tests/test_multiscale_entropy_auc.py b/junifer/markers/complexity/tests/test_multiscale_entropy_auc.py
@@ -1,18 +1,22 @@
 """Provide test for the AUC of multiscale entropy."""
 
 # Authors: Amir Omidvarnia <[email protected]>
+#          Synchon Mandal <[email protected]>
 # License: AGPL
 
-import os
 from pathlib import Path
 
-from nilearn.maskers import NiftiLabelsMasker
+import pytest
 
-from junifer.data import load_parcellation
-from junifer.datareader import DefaultDataReader
-from junifer.markers import MultiscaleEntropyAUC
-from junifer.storage import SQLiteFeatureStorage
-from junifer.testing.datagrabbers import SPMAuditoryTestingDatagrabber
+
+pytest.importorskip("neurokit2")
+
+from junifer.datareader import DefaultDataReader  # noqa: E402
+from junifer.markers.complexity import MultiscaleEntropyAUC  # noqa: E402
+from junifer.storage import SQLiteFeatureStorage  # noqa: E402
+from junifer.testing.datagrabbers import (  # noqa: E402
+    SPMAuditoryTestingDataGrabber,
+)
 
 
 # Set parcellation
@@ -21,7 +25,7 @@
 
 def test_compute() -> None:
     """Test MultiscaleEntropyAUC compute()."""
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
@@ -30,17 +34,8 @@ def test_compute() -> None:
         marker = MultiscaleEntropyAUC(parcellation=PARCELLATION)
         # Compute the marker
         feature_map = marker.fit_transform(element_data)
-
-    # Load parcellation
-    test_parcellation, _, _ = load_parcellation(PARCELLATION)
-    # Compute the NiftiLabelsMasker
-    test_masker = NiftiLabelsMasker(test_parcellation)
-    test_ts = test_masker.fit_transform(element_data["BOLD"]["data"])
-    _, n_roi = test_ts.shape
-
-    # Assert the dimension of timeseries
-    _, n_roi2 = feature_map["BOLD"]["data"].shape
-    assert n_roi == n_roi2
+        # Assert the dimension of timeseries
+        assert feature_map["BOLD"]["data"].ndim == 2
 
 
 def test_get_output_type() -> None:
@@ -58,18 +53,16 @@ def test_store(tmp_path: Path) -> None:
         The path to the test directory.
 
     """
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
         element_data = DefaultDataReader().fit_transform(element)
         # Initialize the marker
         marker = MultiscaleEntropyAUC(parcellation=PARCELLATION)
-
         # Create storage
-        storage_uri = os.path.join(
-            tmp_path, "test_multiscale_entropy_auc.sqlite"
+        storage = SQLiteFeatureStorage(
+            uri=tmp_path / "test_multiscale_entropy_auc.sqlite"
         )
-        storage = SQLiteFeatureStorage(uri=storage_uri)
         # Compute the marker and store
         marker.fit_transform(input=element_data, storage=storage)
diff --git a/junifer/markers/complexity/tests/test_perm_entropy.py b/junifer/markers/complexity/tests/test_perm_entropy.py
@@ -1,18 +1,22 @@
 """Provide test for permutation entropy."""
 
 # Authors: Amir Omidvarnia <[email protected]>
+#          Synchon Mandal <[email protected]>
 # License: AGPL
 
-import os
 from pathlib import Path
 
-from nilearn.maskers import NiftiLabelsMasker
+import pytest
 
-from junifer.data import load_parcellation
-from junifer.datareader import DefaultDataReader
-from junifer.markers import PermEntropy
-from junifer.storage import SQLiteFeatureStorage
-from junifer.testing.datagrabbers import SPMAuditoryTestingDatagrabber
+
+pytest.importorskip("neurokit2")
+
+from junifer.datareader import DefaultDataReader  # noqa: E402
+from junifer.markers.complexity import PermEntropy  # noqa: E402
+from junifer.storage import SQLiteFeatureStorage  # noqa: E402
+from junifer.testing.datagrabbers import (  # noqa: E402
+    SPMAuditoryTestingDataGrabber,
+)
 
 
 # Set parcellation
@@ -21,7 +25,7 @@
 
 def test_compute() -> None:
     """Test PermEntropy compute()."""
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
@@ -30,17 +34,8 @@ def test_compute() -> None:
         marker = PermEntropy(parcellation=PARCELLATION)
         # Compute the marker
         feature_map = marker.fit_transform(element_data)
-
-    # Load parcellation
-    test_parcellation, _, _ = load_parcellation(PARCELLATION)
-    # Compute the NiftiLabelsMasker
-    test_masker = NiftiLabelsMasker(test_parcellation)
-    test_ts = test_masker.fit_transform(element_data["BOLD"]["data"])
-    _, n_roi = test_ts.shape
-
-    # Assert the dimension of timeseries
-    _, n_roi2 = feature_map["BOLD"]["data"].shape
-    assert n_roi == n_roi2
+        # Assert the dimension of timeseries
+        assert feature_map["BOLD"]["data"].ndim == 2
 
 
 def test_get_output_type() -> None:
@@ -58,16 +53,16 @@ def test_store(tmp_path: Path) -> None:
         The path to the test directory.
 
     """
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
         element_data = DefaultDataReader().fit_transform(element)
         # Initialize the marker
         marker = PermEntropy(parcellation=PARCELLATION)
         # Create storage
-        # Create storage
-        storage_uri = os.path.join(tmp_path, "test_perm_entropy.sqlite")
-        storage = SQLiteFeatureStorage(uri=storage_uri)
+        storage = SQLiteFeatureStorage(
+            uri=tmp_path / "test_perm_entropy.sqlite"
+        )
         # Compute the marker and store
         marker.fit_transform(input=element_data, storage=storage)
diff --git a/junifer/markers/complexity/tests/test_range_entropy.py b/junifer/markers/complexity/tests/test_range_entropy.py
@@ -1,18 +1,23 @@
 """Provide test for range entropy."""
 
 # Authors: Amir Omidvarnia <[email protected]>
+#          Synchon Mandal <[email protected]>
 # License: AGPL
 
-import os
 from pathlib import Path
 
-from nilearn.maskers import NiftiLabelsMasker
+import pytest
 
-from junifer.data import load_parcellation
-from junifer.datareader import DefaultDataReader
-from junifer.markers import RangeEntropy
-from junifer.storage import SQLiteFeatureStorage
-from junifer.testing.datagrabbers import SPMAuditoryTestingDatagrabber
+
+pytest.importorskip("neurokit2")
+
+
+from junifer.datareader import DefaultDataReader  # noqa: E402
+from junifer.markers.complexity import RangeEntropy  # noqa: E402
+from junifer.storage import SQLiteFeatureStorage  # noqa: E402
+from junifer.testing.datagrabbers import (  # noqa: E402
+    SPMAuditoryTestingDataGrabber,
+)
 
 
 # Set parcellation
@@ -21,7 +26,7 @@
 
 def test_compute() -> None:
     """Test RangeEntropy compute()."""
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
@@ -30,17 +35,8 @@ def test_compute() -> None:
         marker = RangeEntropy(parcellation=PARCELLATION)
         # Compute the marker
         feature_map = marker.fit_transform(element_data)
-
-    # Load parcellation
-    test_parcellation, _, _ = load_parcellation(PARCELLATION)
-    # Compute the NiftiLabelsMasker
-    test_masker = NiftiLabelsMasker(test_parcellation)
-    test_ts = test_masker.fit_transform(element_data["BOLD"]["data"])
-    _, n_roi = test_ts.shape
-
-    # Assert the dimension of timeseries
-    _, n_roi2 = feature_map["BOLD"]["data"].shape
-    assert n_roi == n_roi2
+        # Assert the dimension of timeseries
+        assert feature_map["BOLD"]["data"].ndim == 2
 
 
 def test_get_output_type() -> None:
@@ -58,15 +54,16 @@ def test_store(tmp_path: Path) -> None:
         The path to the test directory.
 
     """
-    with SPMAuditoryTestingDatagrabber() as dg:
+    with SPMAuditoryTestingDataGrabber() as dg:
         # Fetch element
         element = dg["sub001"]
         # Fetch element data
         element_data = DefaultDataReader().fit_transform(element)
         # Initialize the marker
         marker = RangeEntropy(parcellation=PARCELLATION)
         # Create storage
-        storage_uri = os.path.join(tmp_path, "test_range_entropy.sqlite")
-        storage = SQLiteFeatureStorage(uri=storage_uri)
+        storage = SQLiteFeatureStorage(
+            uri=tmp_path / "test_range_entropy.sqlite"
+        )
         # Compute the marker and store
         marker.fit_transform(input=element_data, storage=storage)