Create separate mne.stats.erp namespace

doc/api/statistics.rst

@@ -53,7 +53,7 @@ ERP-related statistics:
 .. autosummary::
    :toctree: ../generated/
 
-   compute_sme
+   erp.compute_sme
 
 Compute ``adjacency`` matrices for cluster-level statistics:
 

doc/changes/devel/12707.newfeature.rst

@@ -1 +1 @@
-Add :func:`~mne.stats.compute_sme` to compute the analytical standardized measurement error (SME) as a data quality measure for ERP studies, by `Clemens Brunner`_.
+Add :func:`~mne.stats.erp.compute_sme` to compute the analytical standardized measurement error (SME) as a data quality measure for ERP studies, by `Clemens Brunner`_.

mne/stats/__init__.pyi

@@ -5,7 +5,7 @@ __all__ = [
     "bonferroni_correction",
     "bootstrap_confidence_interval",
     "combine_adjacency",
-    "compute_sme",
+    "erp",
     "f_mway_rm",
     "f_oneway",
     "f_threshold_mway_rm",
@@ -21,6 +21,7 @@ __all__ = [
     "ttest_1samp_no_p",
     "ttest_ind_no_p",
 ]
+from . import erp
 from ._adjacency import combine_adjacency
 from .cluster_level import (
     _st_mask_from_s_inds,
@@ -30,7 +31,6 @@ from .cluster_level import (
     spatio_temporal_cluster_test,
     summarize_clusters_stc,
 )
-from .erp import compute_sme
 from .multi_comp import bonferroni_correction, fdr_correction
 from .parametric import (
     _parametric_ci,

mne/stats/tests/test_erp.py

@@ -0,0 +1,27 @@
+from pathlib import Path
+
+import pytest
+
+from mne import Epochs, read_events
+from mne.io import read_raw_fif
+from mne.stats.erp import compute_sme
+
+base_dir = Path(__file__).parents[2] / "io" / "tests" / "data"
+raw = read_raw_fif(base_dir / "test_raw.fif")
+events = read_events(base_dir / "test-eve.fif")
+
+
+def test_compute_sme():
+    """Test SME computation."""
+    epochs = Epochs(raw, events)
+    sme = compute_sme(epochs, start=0, stop=0.1)
+    assert sme.shape == (376,)
+
+    with pytest.raises(TypeError, match="int or float"):
+        compute_sme(epochs, "0", 0.1)
+    with pytest.raises(TypeError, match="int or float"):
+        compute_sme(epochs, 0, "0.1")
+    with pytest.raises(ValueError, match="out of bounds"):
+        compute_sme(epochs, -1.2, 0.3)
+    with pytest.raises(ValueError, match="out of bounds"):
+        compute_sme(epochs, -0.1, 0.8)

mne/tests/test_epochs.py

@@ -62,7 +62,6 @@
 from mne.event import merge_events
 from mne.io import RawArray, read_raw_fif
 from mne.preprocessing import maxwell_filter
-from mne.stats.erp import compute_sme
 from mne.utils import (
     _dt_to_stamp,
     _record_warnings,
@@ -5264,20 +5263,3 @@ def test_empty_error(method, epochs_empty):
         pytest.importorskip("pandas")
     with pytest.raises(RuntimeError, match="is empty."):
         getattr(epochs_empty.copy(), method[0])(**method[1])
-
-
-def test_epochs_sme():
-    """Test SME computation."""
-    raw, events, _ = _get_data()
-    epochs = Epochs(raw, events)
-    sme = compute_sme(epochs, start=0, stop=0.1)
-    assert sme.shape == (376,)
-
-    with pytest.raises(TypeError, match="int or float"):
-        compute_sme(epochs, "0", 0.1)
-    with pytest.raises(TypeError, match="int or float"):
-        compute_sme(epochs, 0, "0.1")
-    with pytest.raises(ValueError, match="out of bounds"):
-        compute_sme(epochs, -1.2, 0.3)
-    with pytest.raises(ValueError, match="out of bounds"):
-        compute_sme(epochs, -0.1, 0.8)