Revert "Improve docstring."

This reverts commit c3b7e20.

Author: jtlait

eis_toolkit/utilities/aitchison_geometry.py

@@ -1,47 +1,45 @@
-from numbers import Number
-
-import numpy as np
-import pandas as pd
-from beartype import beartype
-from beartype.typing import Optional
-
-
-@beartype
-def _normalize(row: pd.Series, sum_value: Number = 1.0) -> pd.Series:
-    """
-    Normalize the series to a given value.
-
-    If no value is provided, normalize to 1.
-
-    Args:
-        row: The series to normalize.
-
-    Returns:
-        A series containing the normalized values.
-    """
-    scale = np.float64(np.sum(row)) / sum_value
-    return np.divide(row, scale)
-
-
-@beartype
-def _closure(df: pd.DataFrame, scale: Optional[Number] = None) -> pd.DataFrame:
-    """
-    Perform the closure operation on the dataframe.
-
-    If a scale value representing the constant sum is not provided, assumes the standard simplex,
-    in which the sum of th components of each composition vector is 1.
-
-    Args:
-        df: A dataframe of shape (N, D) compositional data.
-        scale: The sum to which each data row should result to. Default is 1.
-
-    Returns:
-        A new dataframe of shape (N, D) where each row has been normalized to the given scale value.
-    """
-
-    dfc = df.copy()
-
-    for idx, row in df.iterrows():
-        dfc.iloc[idx] = _normalize(row, scale) if scale is not None else _normalize(row)
-
-    return dfc
+from numbers import Number
+
+import numpy as np
+import pandas as pd
+from beartype import beartype
+from beartype.typing import Optional
+
+
+@beartype
+def _normalize(row: pd.Series, sum_value: Number = 1.0) -> pd.Series:
+    """
+    Normalize the series to a given value.
+
+    If no value is provided, normalize to 1.
+
+    Args:
+        row: The series to normalize.
+
+    Returns:
+        A series containing the normalized values.
+    """
+    scale = np.float64(np.sum(row)) / sum_value
+    return np.divide(row, scale)
+
+
+@beartype
+def _closure(df: pd.DataFrame, scale: Optional[Number] = None) -> pd.DataFrame:
+    """
+    Perform the closure operation on the dataframe.
+
+    Assumes the standard simplex, in which the sum of the components of each composition vector is 1.
+
+    Args:
+        df: A dataframe of shape (N, D) compositional data.
+
+    Returns:
+        A new dataframe of shape (N, D) where each row has been normalized to 1.
+    """
+
+    dfc = df.copy()
+
+    for idx, row in df.iterrows():
+        dfc.iloc[idx] = _normalize(row, scale) if scale is not None else _normalize(row)
+
+    return dfc