Get docs to build

pyproject.toml

@@ -39,6 +39,7 @@ dev = [
     "pytest-cov",
     "sphinx",
     "sphinxcontrib-apidoc",
+    "sphinx_copybutton",
     "furo",
     "myst_nb",
     "jupyter",

src/redflag/__init__.py

@@ -11,11 +11,17 @@
 from .importance import *
 from .outliers import *
 
-# From https://github.com/pypa/setuptools_scm
-from importlib.metadata import version, PackageNotFoundError
 
+from pkg_resources import get_distribution, DistributionNotFound
 try:
-    __version__ = version("package-name")
-except PackageNotFoundError:
-    # package is not installed
-    pass
+    VERSION = get_distribution(__name__).version
+except DistributionNotFound:
+    try:
+        from ._version import version as VERSION
+    except ImportError:
+        raise ImportError(
+            "Failed to find (autogenerated) _version.py. "
+            "This might be because you are installing from GitHub's tarballs, "
+            "use the PyPI ones."
+            )
+__version__ = VERSION

src/redflag/distributions.py

@@ -258,12 +258,13 @@ def wasserstein(X: ArrayLike,
         pass
 
     if stacked:
-        if not is_standard_normal(first.flat):
-            warnings.warn('First group does not appear to be standardized.', stacklevel=2)
+        # Not sure this test makes sense any more.
+        # if not is_standard_normal(first.flat):
+        #     warnings.warn('First group does not appear to be standardized.', stacklevel=2)
         groups = np.hstack([len(dataset)*[i] for i, dataset in enumerate(X)])
         X = np.vstack(X)
 
-    # Now we can certainly treat X as a 2D array.
+    # Now we can treat X as a 2D array.
     X = np.asarray(X)
     if X.ndim != 2:
         raise ValueError("X must be a 2D array-like.")